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Enhancing a company's profitability and competitiveness using integrated vibration-based maintenance: A case study
European Journal of Operational Research 157 (2004) 643–657 www.elsevier.com/locate/dsw
Production, Manufacturing and Logistics
Enhancing a companyÕs profitability and competitiveness using integrated vibration-based maintenance: A case study Basim Al-Najjar *, Imad Alsyouf Department of Terotechnology, School of Industrial Engineering, V€axj€o University, L€uckligs plats 1, 351 95 V€axj€o, Sweden Received 30 November 2001; accepted 1 April 2003 Available online 12 August 2003
Abstract In this paper a model is developed for identifying, monitoring and improving the economic impact of vibration-based maintenance (VBM). This model provides an additional possibility of identifying where, why and how much capital should be invested, and judges whether or not the investment was cost-effective. The model is further utilised to develop relevant maintenance performance measures. When the model was tested in a Swedish paper mill, the main results were: the average yearly maintenance profit achieved using integrated VBM was at least 3.58 million Swedish kronor (SEK) (approximately US$0.358 million), and average potential savings (economic losses) were around SEK 30 million (US$3 million). Furthermore, the model facilitated identification of problem areas and recognition of where investments should be made. The major conclusion is that the better the data coverage and quality, the greater control is possible over direct maintenance costs, savings and further profits in maintenance. Moreover, using the model it would be easier and more reliable to detect deviations in the maintenance performance and eliminate their causes at an early stage. Ó 2003 Elsevier B.V. All rights reserved. Keywords: Productivity and competitiveness; Maintenance; Life cycle cost (LCC); Cost–benefit analysis; Integrated vibration-based maintenance
1. Introduction Maintenance-related costs are usually divided into direct and indirect costs without considering maintenance savings and profits. This in turn falsely implies that maintenance is no more than a cost centre, while the economic benefits that could be gained by more efficient maintenance can be
*
Corresponding author. Tel.: +46-470-70-8422; fax: +46470-76-8540. E-mail address: [email protected] (B. Al-Najjar).
found as savings in the results of other working areas such as production, quality and capital tied up in equipment and spare part redundancies. Mckone and Weiss (1998) cited that the amount of money spent company-wide on maintenance by du Pont in 1991 was roughly equal to its net income. The total indirect maintenance costs, such as loss of income due to breakdowns, poor quality, loss of customers and market shares are, in many cases, difficult to estimate. The economic influence of maintenance in Swedish industry, i.e. the direct and indirect costs, was estimated in AhlmannÕs, 1998 study to be around SEK 190–200 billion
0377-2217/$ - see front matter Ó 2003 Elsevier B.V. All rights reserved. doi:10.1016/S0377-2217(03)00258-3
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annually. On average, the direct maintenance costs constitute approximately half the total maintenance costs (Ahlmann, 1998). In LjungbergÕs (1998) case study conducted at a Swedish car factory, the overall equipment effectiveness (OEE) was estimated to be on average around 55%. Therefore, industry could increase its production capacity without investing in new machinery if an efficient maintenance policy is implemented. A literature survey was carried out using the databases Emerald, ABI/Inform and the Applied Science and Technology Index. The search was performed using different combinations of keywords, such as maintenance, maintenance costs, maintenance savings and maintenance profit. Many researchers have discussed the savings, gains or profits that could be realised by implementing a more efficient maintenance approach. These include, among others, Ahlmann (1984, 1998), Maggard and Rhyne (1992), Foelkel (1998), Coetzee (1999), Walsh (1999), Miller (2000), Ralph (2000), Carter (2001), Kutucuoglu et al. (2001) and Swanson (2001). However, the studies do not discuss how to calculate and or estimate these cost factors, or where to find the required information parameters from the available accountancy system. This is because the impact of the maintenance function can be found in many areas in a company, such as production, quality and production logistics. Furthermore, when a breakdown occurs, it is often easy to point to a lack of maintenance. When breakdowns do not occur, however, it is difficult to prove that maintenance prevented them, as found by Al-Najjar (2000a), Al-Najjar et al. (2001) and Waeyenbergh and Pintelon (2002). The most popular maintenance approaches, i.e. strategies, policies, methodologies or philosophies, are failure-based maintenance, preventive maintenance, condition-based maintenance (of which VBM is an example), reliability-centred maintenance and total productive maintenance. Research into these approaches has been conducted by Moubray (1991), Dekker (1996), Al-Najjar (1997), Mckone and Weiss (1998), Sherwin (2000) and Swanson (2001) among others. Today, based on experience and the use of the most efficient maintenance approach, failure can
be reduced almost to zero. Planned maintenance stoppages can also be reduced by making use of integrated plant-wide condition monitoring and process data, as found in Kerstein (1989), AlNajjar (1997) and Anon (1998). VBM is becoming more widespread, especially where downtime costs are high. Research by Collacott (1977), Al-Najjar (1997, 1998) and DeBotton et al. (2000) highlights the tremendous possibilities of VBM, one of which is the ability to receive indications of changes of the condition of a machine at an early stage. Furthermore, these indications can be of great importance in the early detection of deviations in product quality and therefore in identifying problems before they show on quality control charts, as discussed by Al-Najjar (1996, 1997, 2001) and Olney and Swanson (2002). The precision of the assessment of machine condition and what actions have to be taken depend upon the technical efficiency and the precision of the condition monitoring system itself, according to Al-Najjar (1998, 2000a). Higher precision of machine condition assessment results in fewer stoppages and better product quality. This helps plants to reduce maintenance costs, implement more efficient practices, optimise the workforce and also make a worthwhile contribution to bottom-line performance, as discussed by Anon (1998) and Grall et al. (2002). Life cycle cost (LCC) is defined in the British Standards BS 3811:1993 as the total cost of ownership of an item, taking into account all the costs of acquisition, personnel training, operation, maintenance, modification and disposal. It has been widely used in acquisition of the most effective assets over the long term, see Fabrycky and Blanchard (1990), Ahlmann (1998), Al-Najjar (1999) and Waeyenbergh and Pintelon (2002). In this study, we focus more on identifying the cost factors in LCC and on describing their behaviour during equipment life, so that it will be possible to continually improve a companyÕs profits by monitoring different cost factors and identifying problem areas in the process. Economic benefits gained as a result of improvements in VBM performance can be found in a wide range of plant activities and disciplines, such as production, quality and production logistics; nevertheless, it is
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difficult to specify and quantify the maintenance impact on these activities. This could be considered one of the reasons why maintenance is regarded as a cost centre rather than a profit centre, especially when maintenance demands investment, as is the case with VBM.
2. Maintenance costs and potential savings In this study, direct maintenance costs consist of two major cost categories, which are influenced by internal and external factors. They are: 1. The internal capacity costs needed for the maintenance function to perform its stated objectives, such as direct labour, direct materials (e.g. spare parts), and overheads such as tools, instruments, training, administration and other maintenance-related expenses. 2. The external capacity offered by the original equipment manufacturers or others, i.e. outsourcing. Indirect costs are all the expenses that are indirectly related to maintenance. These could be attributable to issues such as lost profit due to missing production during planned and unplanned stoppages, loss of customers, reputation and consequently loss of market share because of maintenance-related factors resulting in delivery delay and poor quality. Usually, it is difficult to estimate all these costs (particularly in areas such as those related to customer, market and reputation losses); however, with the introduction in recent years of company-wide information (IT) systems, much of the necessary information can be found. The stop that occurs when a machine is halted for maintenance after detecting an imminent failure, which was not identified earlier due to faults in the monitoring system, is defined by Al-Najjar (1997) as unplanned-but-before-failure replacements (UPBFR). In general, the majority of the indirect costs listed below are due to failures, UPBFR, and short stoppages resulting from maintenance performance deficiencies, as discussed in Al-Najjar (2000b). These indirect costs are:
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1. Unavailability cost due to failure and UPBFR. 2. Performance inefficiency costs due to idling, minor stoppages (short stoppages) and reduced speed. 3. Poor quality costs due to maintenance deficiency. 4. Idle fixed cost resources such as idle machines and idle worker costs during breakdowns. 5. Delivery delay penalty costs due to unplanned downtime. 6. Warranty claims from dissatisfied customers due to maintenance-related poor quality, e.g. compensation for product liabilities and repair. 7. Customer dissatisfaction costs due to maintenance-related poor quality, delivery delay or other reasons. 8. Extra energy cost due to disproportional energy consumption. Rao (1993) states that savings of up to 20% on total energy consumption in the UK could be achieved by employing efficient monitoring and management strategies. 9. Accelerated wear due to lack of or inefficient maintenance. 10. Excessive, spare parts, buffer and work-in-progress (WIP) inventory costs to avoid the effect of unplanned stoppages on fulfilling delivery schedules. 11. Unnecessary equipment redundancy costs to avoid waiting time after equipment failure or due to UPBFR. 12. Extra investments needed to preserve WIP and redundancies in good conditions. 13. Extra costs due to the absence of professional labour as a result of maintenance-based accidents such as compensation labour costs and costs of using less skilled labour. 14. Penalties for environmental pollution caused by poor equipment condition and accidents related to inefficient maintenance. 15. Extra insurance premiums due to the increased number of accidents related to inefficient maintenance and their consequences. The importance of these costs may differ among companies; however, all should be considered when evaluating the role of maintenance because they represent the majority of economic losses (potential savings) a manufacturing company may
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encounter and can be recovered by implementing a more efficient maintenance policy. It is for this reason that we label the economic losses as potential savings.
3. Assessment of savings resulting from maintenance LCC is usually divided into acquisition cost (AC), operating cost (OC), support cost (SC), unavailability cost (UC), indirect losses (IL), modification cost (MC) and termination cost (TC) (see Eq. (1)):
(3) Reducing total operating costs. This can be achieved when high confidence in the implemented maintenance policy is created due to its ability to avoid production disturbances and continually reduce the probability of failures and other unplanned stoppages. Thus, the following can be achieved: (i) Maintaining or increasing production speed. (ii) Reducing tied capital in extra inventory of for example raw materials, WIP, finished goods, spare parts and redundant equipment. (iii) Lower insurance premiums due to fewer failure-related accidents.
LCC ¼ AC þ OC þ SC þ UC þ IL þ MC þ TC: ð1Þ Considering LCC factors, it is apparent that they are influenced by the SC (of which maintenance cost is an example, which itself includes various cost factors). Several of the maintenance cost factors such as labour and spare part costs can be directly related to maintenance activities. Other (indirect) costs such as maintenance-related rejected items, losses in market share and reputation are hardly to be found in the accountancy system without being confused with other costs. Based on the available databases, it is unlikely that all the indirect cost factors can easily be assessed and related to maintenance in the same way that losses in production due to failures and short stoppages are assessed and related. To evaluate the economic importance of maintenance activities and the economic impact of investments in maintenance, it is often necessary to assess the life cycle income (LCI). One way to do this is to assess the savings achieved by a more efficient maintenance policy by analysing LCC and the transactions between maintenance and other disciplines within the plant, such as production, quality, and inventories expenses. These savings are usually achieved through: (1) Reducing the downtime generated by failures, UPBFR and planned replacements and repair, i.e. increasing production time. (2) Reducing the number of rejected items due to lack of or inefficient maintenance, i.e. increasing the quality rate.
(4) Less delivery delay, i.e. more accurate delivery schedules. This can be approached by improving machine reliability and OEE by using an efficient and continually improved maintenance policy to detect deviations (and eliminate causes) in machine condition at an early stage. This means increased market share and an enhanced reputation for the company. The assessment of the savings achieved by more efficient maintenance is easier if one assesses LCI compared with the case when the companyÕs profit is generally considered for assessment. In the latter case, several external factors, irrelevant to the maintenance role but which have an appreciable effect on areas such as profit margin and product price, are usually incorporated. These external factors involve: 1. Currency value in the international market, which is usually not stable. 2. Worldwide political crises and wars influencing the cost of input resources such as raw materials, machines and energy. 3. New discoveries and products and new competitors. 4. New national or international regulations, e.g. those related to the environment. Discussing solely direct and indirect maintenance costs is the first step to emphasising the claim that maintenance is more or less a cost centre. In a recession, companies generally reduce the maintenance budget regardless of the benefits
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Fig. 1. The role of maintenance in reducing production cost and increasing plant profit.
it generates for production, quality, safety and the environment for example. Furthermore, the usual and uninformed question from managers––ÔWhy are we paying so much for maintenance when the plant does not have many failures and production interruptions?Õ––is asked without realising the role more efficient maintenance has in achieving these results. In this paper we attempt to introduce a new perspective in order to place maintenance in its proper position among plant activities (see Fig. 1), while considering whether more or less funding should be invested in maintenance during recessions.
4. Technical and economic effectiveness Plant value-adding activities are usually monitored by technical measures such as OEE. Usually the development of OEE and its elements is observed, but when considered in conjunction with total production cost or with plant profits, the company can also assess how to reduce production cost while still satisfying customers, shareholders and society, thus increasing company sales and market share. To survive strong competition, companies need to continually improve their manufacturing pro-
cesses and profitability. Continual improvement demands effective tools for measuring and analysing data, results presentation, optimisation (and sub-optimisation) and reliable decision-making procedures. In general, the quality rate is influenced by many factors. Some of these are related to machine design and construction, raw materials, cutting tools, the environment, the quality control system, company culture etc. The others arise because of the implemented maintenance policy, service and maintenance performance quality. In many cases, especially when there are long-term (chronic) problems, quality problems are a result of particular combinations of some of the factors mentioned above. This means that high quality input elements required for establishing a manufacturing process should be maintained in order to secure a high quality product at a competitive price through high availability and stable product quality (quality variation within narrow limits). As found by Al-Najjar (2000a), these cannot be secured without an effective maintenance policy. Such a policy would be very useful in reducing unplanned stoppages and enhancing performance efficiency of the production process, while fewer failures and better control of the production plant would help minimise pollution and fulfil societyÕs
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demands. In general, these results can be achieved by the following steps: 1. Satisfying customers. 2. Ensuring societyÕs gradual (and wide) acceptance of the company and its products. 3. Increasing share value, therefore satisfying shareholders and increasing share demand. This, in turn, leads to an additional increase in share value. Note that along all these steps profit is generated, because the more customers are satisfied and the company and its products are accepted by society, the more the share value increases and the greater profit can be gained, and vice versa.
5. A model for assessing and monitoring maintenance cost, savings and profits 5.1. Model elements First, the modelÕs cost factors are identified, from which the relevant technical and economic input data are determined. The next step is to know where to find these input data in the accountancy system used. Then, suitable formulas are used to assess the following modelÕs output, as shown in Fig. 2:
(A) Maintenance-related economic losses (potential savings) are the summation of all the economic losses that have occurred due to factors related to maintenance actions, such as unavailability (failures and UPBFR), performance inefficiency (short stoppages), poor quality, and other factors illustrated in Section 2. (B) Direct maintenance cost is the maintenance cost (direct labour, material and overheads) that usually appears in the budget of the maintenance department. It includes both the in-house and outsourced maintenance costs. (C) Investment in maintenance is usually counted as part of the direct maintenance cost. It includes all the expenses spent in developing the maintenance department, such as new facilities, tools, software, IT systems and training. These investments are intended to enhance the performance of the production process and the companyÕs profitability and competitiveness. (D) Maintenance savings are the sum of all the savings that could be achieved by the implementation of a more efficient maintenance policy. For example, VBM could be used to assess the systemÕs equipment or component condition in order to determine the required maintenance tasks prior to any predicted failure. If the maintenance tasks, which are determined based on VBM recommendations, are performed at the stoppages planned by the production department, such as those for cleaning,
Fig. 2. Maintenance cost, savings and profits model.
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shift, batch or tool changes, then the time spent on performing these maintenance tasks could be used to assess the maintenance savings. If, however, these maintenance tasks are not performed in conjunction with the production departmentÕs planned stoppages, failures could occur during the planned production time. The time required for restoring the machine after each such failure is actually the reward, i.e. additional production time acquired by a more efficient maintenance policy. The more parallel the maintenance tasks performed during planned stoppages, the more savings could be achieved. (E) Maintenance profit is the difference between the maintenance savings estimated during a certain period, e.g. one year, and the investments made in maintenance for improving maintenance efficiency, productivity and the companyÕs profitability during the same period. (F) Maintenance performance measures area set of performance measures that could be developed based on the modelÕs inputs and outputs and other relevant raw data. 5.2. Model development Although most of the information required for assessing the cost factors is usually available in a companyÕs databases, some of it is confused with other cost factors and should be assessed. This is why we may lose some certainty in the values of these cost factors when assessing them. The technical and economic input data are used to calculate or assess the maintenance-related potential savings, i.e. production losses, direct maintenance cost, investments in maintenance and minimum savings that have been achieved by a more efficient maintenance policy, such as a VBM policy. Knowledge of the maintenance investments and the minimum savings achieved by a more efficient maintenance policy allows the maintenance profit to be estimated. Moreover, based on the available data concerning the potential savings and other relevant information parameters, a set of relevant maintenance performance measures can be identified and calculated. Trends in the maintenance cost factors and performance measures can then easily be obtained for the study period from the available data, both past and current.
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Furthermore, using analysis tools such as a Pareto diagram helps the decision-maker to identify the problem areas and perform the continual improvement process, i.e. KAIZEN, which is based on the Deming cycle Plan–Do–Check–Act, see Deming (1988) and Oakland (1995). This can be based on performing a technical analysis to relate problems and their causes to the expected results that might be achieved by means of new investments, i.e. to describe which economic losses can be eliminated by performing particular improvements in the maintenance policy. For example, when using a new monitoring and diagnosis system that improves the detection and localisation of damages, fewer failures and UPBFR should then be expected. According to Al-Najjar (1998), the precision of the vibration monitoring system, and consequently VBM efficiency, can be continually improved by making use of integrated and relevant plant-wide information. As found in Al-NajjarÕs (2002) study, comparison between the expected and achieved results is a reliable indication of the cost-effectiveness of an investment. This will improve the answers to the following questions: where, when and why should the next investment be made? All the maintenance tasks that are scheduled based on equipment or component condition, such as condition-based replacements (CBR) of rolling element bearings, are usually recommended by VBM after detecting any damage. In order to assess the savings generated by implementing more efficient maintenance, we consider all the CBR tasks performed during production-determined planned stoppages (those stoppages scheduled by production for carrying out some other tasks) as avoided failures. These replacements are made in parallel during planned stoppages to avoid failures and to utilise the planned stoppage time intensively. Therefore, all the corresponding costs such as profit losses and unutilised fixed costs during the performed CBR tasks could be counted as savings. These savings are regarded as a minimum because if the replaced components were to fail during the planned operating time, they would probably occur separately; consequently, the amount of time required to perform the task would be greater.
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5.3. What is new in this model and its benefits In general, even for new machines, maintenance is central to maintaining a machineÕs technical specifications and fulfilling a companyÕs requirements in producing a particular product with a specified quality and at a predetermined cost. Otherwise, degradation of these specifications can be accelerated during operating time, which means that the machineÕs ability to fulfil company requirements decreases faster. This situation is unacceptable in sectors with intensive capital investment such as process and chemical industries. Therefore, the direct maintenance cost is the minimum required expense to maintain machine quality and fulfil production requirements. During operating time, however, deterioration of the significant components of the machine is unavoidable, even if it is possible in some cases to temporarily arrest the process. Consequently, further production losses can be expected. In addition, changes and variations in the operating and environmental conditions, structural changes in the machine, variations in the use of the machine etc., usually lead to further disturbances and additional economic losses. All of these economic losses motivate special investments to improve the machine, process and operating and environmental conditions in order to reduce these losses. The reduction in the economic losses is called a saving, i.e. maintenance-related recoverable expenses. In this case, it is equal to the difference in the economic losses (potential savings) of two following periods if no other investments such as those in quality, production procedure and instructions (in addition to that investment made in maintenance) have influenced some or all of the savings. As long as it is possible to reduce economic losses by reducing failures, short and planned stoppages and decreasing stoppage times by improving repair, these are recoverable expenses (savings). In other words, by means of a more efficient maintenance policy, some of the economic losses can always be recovered. The model presented in Fig. 2 can be utilised to achieve the following: 1. Keeping track of the minimum savings being generated by more efficient maintenance with
2.
3.
4.
5.
improved performance, which is not possible otherwise. Identifying where, how, why and to what extent a new investment should be made, which could be performed easily when the minimum savings are classified with respect to the basic cost and potential saving factors. Revealing whether or not the investment made to improve maintenance policy was cost-effective. This could be carried out by comparing the achieved savings with the investment. Developing and using relevant performance measures by utilising the available data to detect deviations in the technical and economic effectiveness of the maintenance and manufacturing process before deviations become intolerable. Achieving the continual improvement process, i.e. KAIZEN, cost-effectively.
The new elements in this model can be summarised as follows: (1) Monitoring changes in the relevant maintenance direct cost and potential saving factors, which can be identified in (or estimated from) the existing accountancy system of most companies. (2) The direct maintenance cost cannot be reduced to zero even if all the losses are eliminated. These costs are required to keep the condition and quality of machinery high enough to fulfil the companyÕs requirements, while the investments in maintenance are meant to improve the maintenance policy and overall company performance, thus reducing economic losses. Therefore, the minimum savings would be considered to justify these investments. (3) Using the model, maintenance would be considered as a profit centre instead of cost centre as long as the minimum savings can be identified and monitored against investments.
6. Case study The case study was conducted at StoraEnso Hylte AB (a paper company in Hyltebruk in southern Sweden). The data collected were delimited to stoppages of mechanical components, which were (or could be) monitored by vibration
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stoppages and the quantity of poor quality products resulting from maintenance deficiency (see Table 1). The economic data included parameters such as direct maintenance costs, fixed and variable operating costs, profit margin, net profit, working capital, investments in maintenance, and spare parts inventory (see Table 2). To increase data reliability, all the terms were discussed, explained and agreed upon by the company personnel involved in the case study. Furthermore, the data sheet was adapted to suit the terminology and context of the company. As the economic data were confidential, the data used in the analysis were transformed using several suitable factors which still allowed accurate analysis.
signals. The study was conducted at PM2, one of the companyÕs four machines, which was selected because of its valuable database, particularly during the period studied (1997–2000). A special data sheet was designed for manually collecting the relevant technical and economic information parameters from the company databases. We believe that possible reasons for the unavailability of certain data are that these data had not been required before for analysis or were hidden or confused with other data. 6.1. Data gathering Data were gathered using a special data sheet, designed to collect the required relevant input data. It consisted of two parts––technical and economic. The technical data included parameters such as planned production time, planned production rate, time and frequency of planned stoppages (in which bearings were replaced as a result of using VBM), failures and UPBFR, short
6.2. Model validation, analysis and results The conceptual model was validated using the data collected from the case company. The first
Table 1 The technical data sheet Technical data Planned yearly working hours Yearly planned vacations and holidays Theoretical production rate
2 3 4 5 6 7
NOTES
month
week
day
month
Production Rejected output quantity
day
Driving Up Time
Repair Time
Driving down Time
Waiting Time for resources (Mtrl or experts)
Short Stoppages
Fault seeking
NOTES
ton/hr
Total stoppage duration (min) Waiting time
Maintenance Personnel Response Time
Planned Maintenance
Date
UPBFR (unplanned but before failure replacement)
Stoppage
Transducer position
Time
Week No.
day
1
Stoppage Type Downtime
Unplanned maintenance
year
Vibr. Measure.
Maint. Personnel Response Time (m/c working)
PRODUCT
hours hours
week
MACHINE
651
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Table 2 The economic data sheet
Economical data
factor was the direct maintenance cost of the mechanical components, which was almost constant over the study period with an average of approximately SEK 13 million (US$1.3 million), as illustrated by Fig. 3. The total maintenance investment in PM2 both in general and in training increased between 1997 and 1999, with a small decrease in 2000, as shown in Fig. 4. On average it was approximately SEK 0.455 million (US$45 500) per year. The total economic losses (potential savings) consist of the summation of profit losses and the costs of unutilised resources, for example the fixed cost of an idle machine in the time when the ma-
insurance premium
energy costs
spare parts inventory
investment interest rate
NOTES
maintenance investments
variable operating costs
fixed operating costs
profit margin
injury costs
General economic data
environmental cost
penalty cost due to late delivery)
lost production during stoppage
cost of rework of defected items
maintenance Indirect costs
idle machine (depreciation)
outsourcing
overheads (tools, management, etc)
spare parts
man-hour
Maintenance Direct costs
chine is not producing due to failures, UPBFR, planned stoppages and short stoppages. Also considered as part of the potential savings are the economic losses due to poor quality products caused by maintenance deficiency and tied capital due to extra spare parts inventory. On average, the total potential saving approximated SEK 30 million (US$3 million) and was increasing, as shown in Fig. 5. A Pareto diagram for the elements of the total economic losses (potential savings) is shown in Fig. 6. We can see that the losses due to short stoppages represent the highest value, followed by planned stoppages, quality problems, failures and
B. Al-Najjar, I. Alsyouf / European Journal of Operational Research 157 (2004) 643–657 Maintenance Mechanical Direct Costs for PM2 16 14 12 10 8 6 4 2 0
MSEK
20 18
653
Pareto Diagram for the Average Values of Losses and their Causes 17.302
16 14
Maintenance Mechanical Direct Costs for PM2
1997 12.351
1998 13.893
1999 11.166
2000
14.522
M S E K
12 10
9.565
8 6 4 2
1.699
1.091
0.410
0
Fig. 3. Direct maintenance costs of mechanical components.
Fig. 6. Pareto diagram for the total losses elements.
MSEK
Total maintenance investments in PM2 0.800 0.700 0.600 0.500 0.400 0.300 0.200 0.100 0.000
General Maintenance investment in PM2 PM2 Maintenance investment in training "COMPETENCE"
1997
1998
1999
Average short stoppages (performance efficiency) losses ‘profit & fixed cost (FC)’ Average unavailability ‘recoverable profit & FC)’ losses due to planned stoppages Average quality losses (profit. FC. and variable cost (VC). Average unavailability losses ‘profit & FC’ due to failures and UPBFR Average tied up capital costs due spare parts inventory
2000
Year
Fig. 4. Total investments in maintenance.
UPBFR and, finally, the tied capital due to the extra spare parts inventory which was calculated with respect to the year 1997. The maintenance department of the company has been implementing VBM for several years. Therefore, their long experience and competence in VBM enabled them to achieve a high technical efficiency and precision. For example, the average number of failures was only one per year, with an
average time of about 1.6 hours. Furthermore, the average number of UPBFRs was approximately 3.25 per year, with an average time of about 4.07 hours per stop. Moreover, they managed to integrate VBM with the production schedule. According to the production schedule, the paper machine was stopped every other week for an average of around eight hours for technical production reasons. The maintenance department therefore planned and performed an average of 12 replacements of rolling element bearings per year based on VBM recommendations in the time window initiated by the production department. Consequently, the minimum saving achieved by performing these maintenance tasks was estimated to be on average approximately SEK 4 million (US$0.4 million). As shown in Fig. 7, these savings were increasing in 1999 and 2000. The last factor is maintenance profit, which represents the difference between the minimum savings and maintenance
Potential savings (Total losses) 37.8
40.0 32.0
35.0
31.9
MSEK
30.0 25.0 20.0
18.5
15.0 10.0 5.0 0.0 1997
1998
1999
2000
year
Fig. 5. Total potential savings (economic losses).
Fig. 7. Minimum savings due to more efficient maintenance.
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investments: on average it was around SEK 3.58 million (US$0.358 million).
Total losses(profit+resources) per ton of paper produced (SEK/ton) 250
6.3. Performance measures SEK/ton
Twelve maintenance performance measures were developed and used. The first performance measure is the direct mechanical maintenance cost, i.e. the maintenance cost of the mechanical components that were maintained by VBM. The second performance measure is the total maintenance investment, i.e. the yearly investment spent on improving the competence and the systems of maintenance function. Both the first and second performance measures were shown in Figs. 3 and 4 respectively. The third, fourth and fifth measures are the ratio of the direct mechanical maintenance costs to operation cost, running time and passed (i.e. by quality control) product, which showed approximately the same trend (almost constant) during 1997–2000, as illustrated in Fig. 8. The sixth measure, shown in Fig. 9, is the total economic losses (in profit and resources) per ton of paper produced with accepted quality. It shows that on average approximately SEK 168 were lost for each ton of paper, and also the trend of losses increased. The seventh measure is the minimum savings divided by the tons of paper produced with accepted quality. The eighth measure is the ratio of maintenance investments to potential savings. It was appreciably small and varied between 1% and 2.2%. The ninth measure is the ratio of minimum
200 150 100 50 0 1997
1998
1999
2000
Year
Fig. 9. Total losses per ton of paper produced with accepted quality.
savings to total maintenance investments, shown in Fig. 10. On average it was around 9.2, which can be considered very high in comparison with the range achieved and published internationally, i.e. 5–10, see for example Nicholls (1989). The tenth measure is the ratio of lost profit to actual profit. We noticed that on average a value of around 3.5% of the actual generated profit could have been gained if, ideally, all the failures, UPBFR and short stoppages had been avoided using an efficient maintenance policy. It should be noted that the unproduced quantities during the planned stoppage time are not included. The eleventh measure is the restricted overall process effectiveness (ROPE). ROPE is equivalent to the OEE but restricted to when the machine is subject to mechanical faults that can be maintained by VBM. Finally, the last measure repre-
Ratio of minimum savings to maintenance investment 14.00 12.00 10.00 8.00 6.00 4.00 2.00 0.00 1997
1998
1999
2000
Year
Fig. 8. Maintenance mechanical direct cost to total running time.
Fig. 10. Minimum savings to total maintenance investment.
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sents the value of ROPE, divided by the direct mechanical maintenance costs.
These results are essential to achieve cost-effective continual improvement.
6.4. Benefits of collecting and treating company data in this way
7. Conclusions
Using the data collected in the technical and economic parts of the developed datasheet allowed us to achieve completely different results compared to those achieved by the company using their own information parameters. The benefits of applying the model and its new datasheet were described in Section 5.1. The results that are usually achieved based on the available databases are summarised below: 1. Frequency and duration of total stoppage time classified according to its different types, such as planned, unplanned and short stoppages. 2. Total poor quality quantities. 3. General economic data such as those used in annual reports, e.g. balance sheet, profit and loss statements. Using the current databases (directly), it is not possible to obtain detailed estimates of the economic consequences of the various production stoppages, poor quality and other cost factors such as tied capital in spare parts inventory. Furthermore, it is impossible to obtain the detailed elements of each stoppage time. Additionally, it is not straightforward to find detailed information about investments made, for example in the maintenance department, since they are registered as expenses in different accounts. This means that the company lacks the opportunity to achieve results such as: 1. Estimating and prioritising the various types of savings, e.g. as economic losses that could be achieved partially or completely by implementing a more efficient maintenance policy. 2. Identifying and tracing the real causes of the production losses, knowing how much and where investment should be allocated, and whether it is cost effective. 3. Obtaining the data required to monitor and control the performance of the maintenance and manufacturing process.
Using the model means that LCC factors will be used as monitoring parameters to provide the required information for decision-making, to ensure cost-effective actions and enhance continual improvement efforts cost-effectively. Applying this model establishes continual improvement as the driving force for more accurate and precise results. Comparing the minimum savings with the investments made for improving maintenance policy reveals how cost-effective the investments in maintenance were and whether or not they were relevant. Applying relevant performance measures helps to detect deviations at an early stage to avoid further economic losses. Finally, in a recession greater investment should be made in maintenance rather than reducing its budget, because investing in maintenance can return nine times the invested capital over the depreciation period. Acknowledgements This paper was one of the results of a project that was financially supported by the Swedish National Board for Industrial and Technical Development, NUTEK, and the Swedish companies StoraEnso Hylte AB, Volvo Truck Components AB in K€ oping, SKF Condition Monitoring, and ABB Alstom Power AB in V€axj€ o. We would like to thank the maintenance department staff at StoraEnso Hylte AB, in particular Mirela Jasarevic, J€ orgen Blomqvist, Bernt Petersson and Jan Andersen. Also, we would like to thank the centre of industrial competitiveness (CIC) at V€axj€ o University for their financial support. References Ahlmann, H., 1984. Maintenance effectiveness and economic models in the terotechnology concept. Maintenance Management International 4, 131–139.
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Ahlmann, H., 1998. The Economic Significance of Maintenance in Industrial Enterprises. Lund University, Lund Institute of Technology, Sweden. Al-Najjar, B., 1996. Total quality maintenance: An approach for continuous reduction in costs of quality products. Journal of Quality in Maintenance Engineering 2 (3), 2– 20. Al-Najjar, B., 1997. Condition-Based Maintenance: Selection and Improvement of a Cost-Effective Vibration-Based Policy in Rolling Element Bearings, Doctoral Thesis, Lund University/LTH, Sweden. Al-Najjar, B., 1998. Improved effectiveness of vibration monitoring of rolling element bearings in paper mills. Journal of Engineering Tribology, ImechE. Proceedings of the Institution of Mechanical Engineers 212 (J), 111–120. Al-Najjar, B., 1999. An approach for continuous reduction in LCC when using integrated vibration-based maintenance: A case study, COMADEM 99, Sunderland University, Sunderland, England, pp. 159–169. Al-Najjar, B., 2000a. Accuracy, effectiveness and improvement of vibration-based maintenance in paper mills: Case studies. Journal of Sound and Vibration 229 (2), 389– 410. Al-Najjar, B., 2000b. Impact of real-time measurements of operating conditions on effectiveness and accuracy of vibration-based maintenance policy: A case study in paper mill. Journal of Quality in Maintenance Engineering 6 (4), 275–287. Al-Najjar, B., 2001. A concept for detecting quality deviation earlier than when using traditional diagram in automotive: A case study. Journal of Quality and Reliability Management 18 (8), 917–940. Al-Najjar, B., 2002. CompanyÕs business and competitiveness enhancement: A model of integrated vibration-based maintenance impact on companyÕs effectiveness. COMADEM, 2–4 September 2002, Birmingham, UK, pp. 238–248. Al-Najjar, B., Alsyouf, I., Salgado, E., Khoshaba, S., Faaborg, K., 2001 Economic importance of maintenance-planning when using vibration-based maintenance policy, V€axj€ o University, LCC project report. Anon, 1998. Integrated plant-wide condition monitoring and process data system. Insight/non-destructive testing and condition monitoring. Journal of the British Institute 40 (12), 809. BS 3811:1993 Glossary of maintenance terms in terotechnology. British Standards Institution, London. Carter, R.A., 2001. Shovel maintenance gains from improved designs, tools and techniques. Elsevier Engineering Information 106 (8), S7. Coetzee, J., 1999. A holistic approach to the maintenance problem. Journal of Quality in Maintenance Engineering 5 (3), 276–280. Collacott, R.A., 1977. Mechanical Fault Diagnosis and Condition Monitoring. Chapman and Hall, London. DeBotton, C., Ben-Ari, J., Sher, E., 2000. Vibration monitoring as a predictive maintenance tool for reciprocating engines.
Proceedings of the Institution of Mechanical Engineers, London (Part D) Journal of Automobile Engineering 214 (8), 895–903. Dekker, R., 1996. Applications of maintenance optimisation models: A review and analysis. Reliability Engineering and System Safety 51, 229–240. Deming, W.E., 1988. Out of the Crisis: Quality, Productivity and Competitive Position. Cambridge University Press, Cambridge. Fabrycky, W.J., Blanchard, B.S., 1990. System Engineering and Analysis. Prentice-Hall Inc., Englewood Cliffs. Foelkel, C., 1998. A business-oriented approach to maintenance. Tappi Journal 81 (September), 67–69. Grall, A., Berenguer, C., Dieulle, L., 2002. A condition-based maintenance policy for stochastically deteriorating systems. Reliability Engineering and System Safety 76, 167–180. Kerstein, H., 1989. Quality improvement through preventive maintenance, ASQC Quality Congress Transactions, Toronto, pp. 402–415. Kutucuoglu, K., Hamali, J., Irani, Z., Sharp, J., 2001. A framework for managing maintenance using performance measurement systems. International Journal of Operations and Production Management 21 (1/2), 173–194. Ljungberg, O., 1998. Measurement of overall equipment effectiveness as a basis for TPM activities. International Journal of Operations and Production Management 18 (5), 495–507. Maggard, B.N., Rhyne, D.M., 1992. Total productive maintenance: A timely integration of production and maintenance. Production and Inventory Management Journal, Alexandria 33 (4), 6–11. Mckone, K., Weiss, E., 1998. TPM: Planned and autonomous maintenance: Bridging the gap between practice and research. Production and Operations Management 7 (4), 335– 351. Miller, D., 2000. Profit from preventive maintenance, Bulk solids handling. Elsevier Engineering Information 20 (1), 57–61. Moubray, J., 1991. Reliability Centred Maintenance. Butterworth Heinemann, Oxford, UK. Nicholls, C., 1989. Cost-effective condition monitoring, NIKAT Associate, Chester, UK, COMADEM International, pp. 335–348. Oakland, J., 1995. Total Quality Management. ButterworthHeinemann, Oxford. Olney, D., Swanson, B., 2002. Vibration monitoring with wireless networks. Quality 41 (6), 42–44. Ralph, W.P., 2000. Maximising value from maintenance operations. Material Handling Management, Cleveland, June. Rao, B.K.N., 1993. Profitable condition monitoring and diagnostic management. In: Profitable Condition Monitoring. Kluwer, London, pp. 37–44. Sherwin, D.J., 2000. A review of overall models for maintenance management. Journal of Quality in Maintenance Engineering 6 (3), 138–164.
B. Al-Najjar, I. Alsyouf / European Journal of Operational Research 157 (2004) 643–657 Swanson, L., 2001. Linking maintenance strategies to performance. International Journal of Production Economics 70, 237–244. Walsh, K., 1999. Predictive maintenance profits from sensor diagnostics. InTech 46 (6), 36–42.
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Waeyenbergh, G., Pintelon, L., 2002. A framework for maintenance concept development. International Journal of Production Economics 77, 299– 313.
Production, Manufacturing and Logistics
Enhancing a companyÕs profitability and competitiveness using integrated vibration-based maintenance: A case study Basim Al-Najjar *, Imad Alsyouf Department of Terotechnology, School of Industrial Engineering, V€axj€o University, L€uckligs plats 1, 351 95 V€axj€o, Sweden Received 30 November 2001; accepted 1 April 2003 Available online 12 August 2003
Abstract In this paper a model is developed for identifying, monitoring and improving the economic impact of vibration-based maintenance (VBM). This model provides an additional possibility of identifying where, why and how much capital should be invested, and judges whether or not the investment was cost-effective. The model is further utilised to develop relevant maintenance performance measures. When the model was tested in a Swedish paper mill, the main results were: the average yearly maintenance profit achieved using integrated VBM was at least 3.58 million Swedish kronor (SEK) (approximately US$0.358 million), and average potential savings (economic losses) were around SEK 30 million (US$3 million). Furthermore, the model facilitated identification of problem areas and recognition of where investments should be made. The major conclusion is that the better the data coverage and quality, the greater control is possible over direct maintenance costs, savings and further profits in maintenance. Moreover, using the model it would be easier and more reliable to detect deviations in the maintenance performance and eliminate their causes at an early stage. Ó 2003 Elsevier B.V. All rights reserved. Keywords: Productivity and competitiveness; Maintenance; Life cycle cost (LCC); Cost–benefit analysis; Integrated vibration-based maintenance
1. Introduction Maintenance-related costs are usually divided into direct and indirect costs without considering maintenance savings and profits. This in turn falsely implies that maintenance is no more than a cost centre, while the economic benefits that could be gained by more efficient maintenance can be
*
Corresponding author. Tel.: +46-470-70-8422; fax: +46470-76-8540. E-mail address: [email protected] (B. Al-Najjar).
found as savings in the results of other working areas such as production, quality and capital tied up in equipment and spare part redundancies. Mckone and Weiss (1998) cited that the amount of money spent company-wide on maintenance by du Pont in 1991 was roughly equal to its net income. The total indirect maintenance costs, such as loss of income due to breakdowns, poor quality, loss of customers and market shares are, in many cases, difficult to estimate. The economic influence of maintenance in Swedish industry, i.e. the direct and indirect costs, was estimated in AhlmannÕs, 1998 study to be around SEK 190–200 billion
0377-2217/$ - see front matter Ó 2003 Elsevier B.V. All rights reserved. doi:10.1016/S0377-2217(03)00258-3
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annually. On average, the direct maintenance costs constitute approximately half the total maintenance costs (Ahlmann, 1998). In LjungbergÕs (1998) case study conducted at a Swedish car factory, the overall equipment effectiveness (OEE) was estimated to be on average around 55%. Therefore, industry could increase its production capacity without investing in new machinery if an efficient maintenance policy is implemented. A literature survey was carried out using the databases Emerald, ABI/Inform and the Applied Science and Technology Index. The search was performed using different combinations of keywords, such as maintenance, maintenance costs, maintenance savings and maintenance profit. Many researchers have discussed the savings, gains or profits that could be realised by implementing a more efficient maintenance approach. These include, among others, Ahlmann (1984, 1998), Maggard and Rhyne (1992), Foelkel (1998), Coetzee (1999), Walsh (1999), Miller (2000), Ralph (2000), Carter (2001), Kutucuoglu et al. (2001) and Swanson (2001). However, the studies do not discuss how to calculate and or estimate these cost factors, or where to find the required information parameters from the available accountancy system. This is because the impact of the maintenance function can be found in many areas in a company, such as production, quality and production logistics. Furthermore, when a breakdown occurs, it is often easy to point to a lack of maintenance. When breakdowns do not occur, however, it is difficult to prove that maintenance prevented them, as found by Al-Najjar (2000a), Al-Najjar et al. (2001) and Waeyenbergh and Pintelon (2002). The most popular maintenance approaches, i.e. strategies, policies, methodologies or philosophies, are failure-based maintenance, preventive maintenance, condition-based maintenance (of which VBM is an example), reliability-centred maintenance and total productive maintenance. Research into these approaches has been conducted by Moubray (1991), Dekker (1996), Al-Najjar (1997), Mckone and Weiss (1998), Sherwin (2000) and Swanson (2001) among others. Today, based on experience and the use of the most efficient maintenance approach, failure can
be reduced almost to zero. Planned maintenance stoppages can also be reduced by making use of integrated plant-wide condition monitoring and process data, as found in Kerstein (1989), AlNajjar (1997) and Anon (1998). VBM is becoming more widespread, especially where downtime costs are high. Research by Collacott (1977), Al-Najjar (1997, 1998) and DeBotton et al. (2000) highlights the tremendous possibilities of VBM, one of which is the ability to receive indications of changes of the condition of a machine at an early stage. Furthermore, these indications can be of great importance in the early detection of deviations in product quality and therefore in identifying problems before they show on quality control charts, as discussed by Al-Najjar (1996, 1997, 2001) and Olney and Swanson (2002). The precision of the assessment of machine condition and what actions have to be taken depend upon the technical efficiency and the precision of the condition monitoring system itself, according to Al-Najjar (1998, 2000a). Higher precision of machine condition assessment results in fewer stoppages and better product quality. This helps plants to reduce maintenance costs, implement more efficient practices, optimise the workforce and also make a worthwhile contribution to bottom-line performance, as discussed by Anon (1998) and Grall et al. (2002). Life cycle cost (LCC) is defined in the British Standards BS 3811:1993 as the total cost of ownership of an item, taking into account all the costs of acquisition, personnel training, operation, maintenance, modification and disposal. It has been widely used in acquisition of the most effective assets over the long term, see Fabrycky and Blanchard (1990), Ahlmann (1998), Al-Najjar (1999) and Waeyenbergh and Pintelon (2002). In this study, we focus more on identifying the cost factors in LCC and on describing their behaviour during equipment life, so that it will be possible to continually improve a companyÕs profits by monitoring different cost factors and identifying problem areas in the process. Economic benefits gained as a result of improvements in VBM performance can be found in a wide range of plant activities and disciplines, such as production, quality and production logistics; nevertheless, it is
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difficult to specify and quantify the maintenance impact on these activities. This could be considered one of the reasons why maintenance is regarded as a cost centre rather than a profit centre, especially when maintenance demands investment, as is the case with VBM.
2. Maintenance costs and potential savings In this study, direct maintenance costs consist of two major cost categories, which are influenced by internal and external factors. They are: 1. The internal capacity costs needed for the maintenance function to perform its stated objectives, such as direct labour, direct materials (e.g. spare parts), and overheads such as tools, instruments, training, administration and other maintenance-related expenses. 2. The external capacity offered by the original equipment manufacturers or others, i.e. outsourcing. Indirect costs are all the expenses that are indirectly related to maintenance. These could be attributable to issues such as lost profit due to missing production during planned and unplanned stoppages, loss of customers, reputation and consequently loss of market share because of maintenance-related factors resulting in delivery delay and poor quality. Usually, it is difficult to estimate all these costs (particularly in areas such as those related to customer, market and reputation losses); however, with the introduction in recent years of company-wide information (IT) systems, much of the necessary information can be found. The stop that occurs when a machine is halted for maintenance after detecting an imminent failure, which was not identified earlier due to faults in the monitoring system, is defined by Al-Najjar (1997) as unplanned-but-before-failure replacements (UPBFR). In general, the majority of the indirect costs listed below are due to failures, UPBFR, and short stoppages resulting from maintenance performance deficiencies, as discussed in Al-Najjar (2000b). These indirect costs are:
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1. Unavailability cost due to failure and UPBFR. 2. Performance inefficiency costs due to idling, minor stoppages (short stoppages) and reduced speed. 3. Poor quality costs due to maintenance deficiency. 4. Idle fixed cost resources such as idle machines and idle worker costs during breakdowns. 5. Delivery delay penalty costs due to unplanned downtime. 6. Warranty claims from dissatisfied customers due to maintenance-related poor quality, e.g. compensation for product liabilities and repair. 7. Customer dissatisfaction costs due to maintenance-related poor quality, delivery delay or other reasons. 8. Extra energy cost due to disproportional energy consumption. Rao (1993) states that savings of up to 20% on total energy consumption in the UK could be achieved by employing efficient monitoring and management strategies. 9. Accelerated wear due to lack of or inefficient maintenance. 10. Excessive, spare parts, buffer and work-in-progress (WIP) inventory costs to avoid the effect of unplanned stoppages on fulfilling delivery schedules. 11. Unnecessary equipment redundancy costs to avoid waiting time after equipment failure or due to UPBFR. 12. Extra investments needed to preserve WIP and redundancies in good conditions. 13. Extra costs due to the absence of professional labour as a result of maintenance-based accidents such as compensation labour costs and costs of using less skilled labour. 14. Penalties for environmental pollution caused by poor equipment condition and accidents related to inefficient maintenance. 15. Extra insurance premiums due to the increased number of accidents related to inefficient maintenance and their consequences. The importance of these costs may differ among companies; however, all should be considered when evaluating the role of maintenance because they represent the majority of economic losses (potential savings) a manufacturing company may
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encounter and can be recovered by implementing a more efficient maintenance policy. It is for this reason that we label the economic losses as potential savings.
3. Assessment of savings resulting from maintenance LCC is usually divided into acquisition cost (AC), operating cost (OC), support cost (SC), unavailability cost (UC), indirect losses (IL), modification cost (MC) and termination cost (TC) (see Eq. (1)):
(3) Reducing total operating costs. This can be achieved when high confidence in the implemented maintenance policy is created due to its ability to avoid production disturbances and continually reduce the probability of failures and other unplanned stoppages. Thus, the following can be achieved: (i) Maintaining or increasing production speed. (ii) Reducing tied capital in extra inventory of for example raw materials, WIP, finished goods, spare parts and redundant equipment. (iii) Lower insurance premiums due to fewer failure-related accidents.
LCC ¼ AC þ OC þ SC þ UC þ IL þ MC þ TC: ð1Þ Considering LCC factors, it is apparent that they are influenced by the SC (of which maintenance cost is an example, which itself includes various cost factors). Several of the maintenance cost factors such as labour and spare part costs can be directly related to maintenance activities. Other (indirect) costs such as maintenance-related rejected items, losses in market share and reputation are hardly to be found in the accountancy system without being confused with other costs. Based on the available databases, it is unlikely that all the indirect cost factors can easily be assessed and related to maintenance in the same way that losses in production due to failures and short stoppages are assessed and related. To evaluate the economic importance of maintenance activities and the economic impact of investments in maintenance, it is often necessary to assess the life cycle income (LCI). One way to do this is to assess the savings achieved by a more efficient maintenance policy by analysing LCC and the transactions between maintenance and other disciplines within the plant, such as production, quality, and inventories expenses. These savings are usually achieved through: (1) Reducing the downtime generated by failures, UPBFR and planned replacements and repair, i.e. increasing production time. (2) Reducing the number of rejected items due to lack of or inefficient maintenance, i.e. increasing the quality rate.
(4) Less delivery delay, i.e. more accurate delivery schedules. This can be approached by improving machine reliability and OEE by using an efficient and continually improved maintenance policy to detect deviations (and eliminate causes) in machine condition at an early stage. This means increased market share and an enhanced reputation for the company. The assessment of the savings achieved by more efficient maintenance is easier if one assesses LCI compared with the case when the companyÕs profit is generally considered for assessment. In the latter case, several external factors, irrelevant to the maintenance role but which have an appreciable effect on areas such as profit margin and product price, are usually incorporated. These external factors involve: 1. Currency value in the international market, which is usually not stable. 2. Worldwide political crises and wars influencing the cost of input resources such as raw materials, machines and energy. 3. New discoveries and products and new competitors. 4. New national or international regulations, e.g. those related to the environment. Discussing solely direct and indirect maintenance costs is the first step to emphasising the claim that maintenance is more or less a cost centre. In a recession, companies generally reduce the maintenance budget regardless of the benefits
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Fig. 1. The role of maintenance in reducing production cost and increasing plant profit.
it generates for production, quality, safety and the environment for example. Furthermore, the usual and uninformed question from managers––ÔWhy are we paying so much for maintenance when the plant does not have many failures and production interruptions?Õ––is asked without realising the role more efficient maintenance has in achieving these results. In this paper we attempt to introduce a new perspective in order to place maintenance in its proper position among plant activities (see Fig. 1), while considering whether more or less funding should be invested in maintenance during recessions.
4. Technical and economic effectiveness Plant value-adding activities are usually monitored by technical measures such as OEE. Usually the development of OEE and its elements is observed, but when considered in conjunction with total production cost or with plant profits, the company can also assess how to reduce production cost while still satisfying customers, shareholders and society, thus increasing company sales and market share. To survive strong competition, companies need to continually improve their manufacturing pro-
cesses and profitability. Continual improvement demands effective tools for measuring and analysing data, results presentation, optimisation (and sub-optimisation) and reliable decision-making procedures. In general, the quality rate is influenced by many factors. Some of these are related to machine design and construction, raw materials, cutting tools, the environment, the quality control system, company culture etc. The others arise because of the implemented maintenance policy, service and maintenance performance quality. In many cases, especially when there are long-term (chronic) problems, quality problems are a result of particular combinations of some of the factors mentioned above. This means that high quality input elements required for establishing a manufacturing process should be maintained in order to secure a high quality product at a competitive price through high availability and stable product quality (quality variation within narrow limits). As found by Al-Najjar (2000a), these cannot be secured without an effective maintenance policy. Such a policy would be very useful in reducing unplanned stoppages and enhancing performance efficiency of the production process, while fewer failures and better control of the production plant would help minimise pollution and fulfil societyÕs
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demands. In general, these results can be achieved by the following steps: 1. Satisfying customers. 2. Ensuring societyÕs gradual (and wide) acceptance of the company and its products. 3. Increasing share value, therefore satisfying shareholders and increasing share demand. This, in turn, leads to an additional increase in share value. Note that along all these steps profit is generated, because the more customers are satisfied and the company and its products are accepted by society, the more the share value increases and the greater profit can be gained, and vice versa.
5. A model for assessing and monitoring maintenance cost, savings and profits 5.1. Model elements First, the modelÕs cost factors are identified, from which the relevant technical and economic input data are determined. The next step is to know where to find these input data in the accountancy system used. Then, suitable formulas are used to assess the following modelÕs output, as shown in Fig. 2:
(A) Maintenance-related economic losses (potential savings) are the summation of all the economic losses that have occurred due to factors related to maintenance actions, such as unavailability (failures and UPBFR), performance inefficiency (short stoppages), poor quality, and other factors illustrated in Section 2. (B) Direct maintenance cost is the maintenance cost (direct labour, material and overheads) that usually appears in the budget of the maintenance department. It includes both the in-house and outsourced maintenance costs. (C) Investment in maintenance is usually counted as part of the direct maintenance cost. It includes all the expenses spent in developing the maintenance department, such as new facilities, tools, software, IT systems and training. These investments are intended to enhance the performance of the production process and the companyÕs profitability and competitiveness. (D) Maintenance savings are the sum of all the savings that could be achieved by the implementation of a more efficient maintenance policy. For example, VBM could be used to assess the systemÕs equipment or component condition in order to determine the required maintenance tasks prior to any predicted failure. If the maintenance tasks, which are determined based on VBM recommendations, are performed at the stoppages planned by the production department, such as those for cleaning,
Fig. 2. Maintenance cost, savings and profits model.
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shift, batch or tool changes, then the time spent on performing these maintenance tasks could be used to assess the maintenance savings. If, however, these maintenance tasks are not performed in conjunction with the production departmentÕs planned stoppages, failures could occur during the planned production time. The time required for restoring the machine after each such failure is actually the reward, i.e. additional production time acquired by a more efficient maintenance policy. The more parallel the maintenance tasks performed during planned stoppages, the more savings could be achieved. (E) Maintenance profit is the difference between the maintenance savings estimated during a certain period, e.g. one year, and the investments made in maintenance for improving maintenance efficiency, productivity and the companyÕs profitability during the same period. (F) Maintenance performance measures area set of performance measures that could be developed based on the modelÕs inputs and outputs and other relevant raw data. 5.2. Model development Although most of the information required for assessing the cost factors is usually available in a companyÕs databases, some of it is confused with other cost factors and should be assessed. This is why we may lose some certainty in the values of these cost factors when assessing them. The technical and economic input data are used to calculate or assess the maintenance-related potential savings, i.e. production losses, direct maintenance cost, investments in maintenance and minimum savings that have been achieved by a more efficient maintenance policy, such as a VBM policy. Knowledge of the maintenance investments and the minimum savings achieved by a more efficient maintenance policy allows the maintenance profit to be estimated. Moreover, based on the available data concerning the potential savings and other relevant information parameters, a set of relevant maintenance performance measures can be identified and calculated. Trends in the maintenance cost factors and performance measures can then easily be obtained for the study period from the available data, both past and current.
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Furthermore, using analysis tools such as a Pareto diagram helps the decision-maker to identify the problem areas and perform the continual improvement process, i.e. KAIZEN, which is based on the Deming cycle Plan–Do–Check–Act, see Deming (1988) and Oakland (1995). This can be based on performing a technical analysis to relate problems and their causes to the expected results that might be achieved by means of new investments, i.e. to describe which economic losses can be eliminated by performing particular improvements in the maintenance policy. For example, when using a new monitoring and diagnosis system that improves the detection and localisation of damages, fewer failures and UPBFR should then be expected. According to Al-Najjar (1998), the precision of the vibration monitoring system, and consequently VBM efficiency, can be continually improved by making use of integrated and relevant plant-wide information. As found in Al-NajjarÕs (2002) study, comparison between the expected and achieved results is a reliable indication of the cost-effectiveness of an investment. This will improve the answers to the following questions: where, when and why should the next investment be made? All the maintenance tasks that are scheduled based on equipment or component condition, such as condition-based replacements (CBR) of rolling element bearings, are usually recommended by VBM after detecting any damage. In order to assess the savings generated by implementing more efficient maintenance, we consider all the CBR tasks performed during production-determined planned stoppages (those stoppages scheduled by production for carrying out some other tasks) as avoided failures. These replacements are made in parallel during planned stoppages to avoid failures and to utilise the planned stoppage time intensively. Therefore, all the corresponding costs such as profit losses and unutilised fixed costs during the performed CBR tasks could be counted as savings. These savings are regarded as a minimum because if the replaced components were to fail during the planned operating time, they would probably occur separately; consequently, the amount of time required to perform the task would be greater.
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5.3. What is new in this model and its benefits In general, even for new machines, maintenance is central to maintaining a machineÕs technical specifications and fulfilling a companyÕs requirements in producing a particular product with a specified quality and at a predetermined cost. Otherwise, degradation of these specifications can be accelerated during operating time, which means that the machineÕs ability to fulfil company requirements decreases faster. This situation is unacceptable in sectors with intensive capital investment such as process and chemical industries. Therefore, the direct maintenance cost is the minimum required expense to maintain machine quality and fulfil production requirements. During operating time, however, deterioration of the significant components of the machine is unavoidable, even if it is possible in some cases to temporarily arrest the process. Consequently, further production losses can be expected. In addition, changes and variations in the operating and environmental conditions, structural changes in the machine, variations in the use of the machine etc., usually lead to further disturbances and additional economic losses. All of these economic losses motivate special investments to improve the machine, process and operating and environmental conditions in order to reduce these losses. The reduction in the economic losses is called a saving, i.e. maintenance-related recoverable expenses. In this case, it is equal to the difference in the economic losses (potential savings) of two following periods if no other investments such as those in quality, production procedure and instructions (in addition to that investment made in maintenance) have influenced some or all of the savings. As long as it is possible to reduce economic losses by reducing failures, short and planned stoppages and decreasing stoppage times by improving repair, these are recoverable expenses (savings). In other words, by means of a more efficient maintenance policy, some of the economic losses can always be recovered. The model presented in Fig. 2 can be utilised to achieve the following: 1. Keeping track of the minimum savings being generated by more efficient maintenance with
2.
3.
4.
5.
improved performance, which is not possible otherwise. Identifying where, how, why and to what extent a new investment should be made, which could be performed easily when the minimum savings are classified with respect to the basic cost and potential saving factors. Revealing whether or not the investment made to improve maintenance policy was cost-effective. This could be carried out by comparing the achieved savings with the investment. Developing and using relevant performance measures by utilising the available data to detect deviations in the technical and economic effectiveness of the maintenance and manufacturing process before deviations become intolerable. Achieving the continual improvement process, i.e. KAIZEN, cost-effectively.
The new elements in this model can be summarised as follows: (1) Monitoring changes in the relevant maintenance direct cost and potential saving factors, which can be identified in (or estimated from) the existing accountancy system of most companies. (2) The direct maintenance cost cannot be reduced to zero even if all the losses are eliminated. These costs are required to keep the condition and quality of machinery high enough to fulfil the companyÕs requirements, while the investments in maintenance are meant to improve the maintenance policy and overall company performance, thus reducing economic losses. Therefore, the minimum savings would be considered to justify these investments. (3) Using the model, maintenance would be considered as a profit centre instead of cost centre as long as the minimum savings can be identified and monitored against investments.
6. Case study The case study was conducted at StoraEnso Hylte AB (a paper company in Hyltebruk in southern Sweden). The data collected were delimited to stoppages of mechanical components, which were (or could be) monitored by vibration
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stoppages and the quantity of poor quality products resulting from maintenance deficiency (see Table 1). The economic data included parameters such as direct maintenance costs, fixed and variable operating costs, profit margin, net profit, working capital, investments in maintenance, and spare parts inventory (see Table 2). To increase data reliability, all the terms were discussed, explained and agreed upon by the company personnel involved in the case study. Furthermore, the data sheet was adapted to suit the terminology and context of the company. As the economic data were confidential, the data used in the analysis were transformed using several suitable factors which still allowed accurate analysis.
signals. The study was conducted at PM2, one of the companyÕs four machines, which was selected because of its valuable database, particularly during the period studied (1997–2000). A special data sheet was designed for manually collecting the relevant technical and economic information parameters from the company databases. We believe that possible reasons for the unavailability of certain data are that these data had not been required before for analysis or were hidden or confused with other data. 6.1. Data gathering Data were gathered using a special data sheet, designed to collect the required relevant input data. It consisted of two parts––technical and economic. The technical data included parameters such as planned production time, planned production rate, time and frequency of planned stoppages (in which bearings were replaced as a result of using VBM), failures and UPBFR, short
6.2. Model validation, analysis and results The conceptual model was validated using the data collected from the case company. The first
Table 1 The technical data sheet Technical data Planned yearly working hours Yearly planned vacations and holidays Theoretical production rate
2 3 4 5 6 7
NOTES
month
week
day
month
Production Rejected output quantity
day
Driving Up Time
Repair Time
Driving down Time
Waiting Time for resources (Mtrl or experts)
Short Stoppages
Fault seeking
NOTES
ton/hr
Total stoppage duration (min) Waiting time
Maintenance Personnel Response Time
Planned Maintenance
Date
UPBFR (unplanned but before failure replacement)
Stoppage
Transducer position
Time
Week No.
day
1
Stoppage Type Downtime
Unplanned maintenance
year
Vibr. Measure.
Maint. Personnel Response Time (m/c working)
PRODUCT
hours hours
week
MACHINE
651
652
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Table 2 The economic data sheet
Economical data
factor was the direct maintenance cost of the mechanical components, which was almost constant over the study period with an average of approximately SEK 13 million (US$1.3 million), as illustrated by Fig. 3. The total maintenance investment in PM2 both in general and in training increased between 1997 and 1999, with a small decrease in 2000, as shown in Fig. 4. On average it was approximately SEK 0.455 million (US$45 500) per year. The total economic losses (potential savings) consist of the summation of profit losses and the costs of unutilised resources, for example the fixed cost of an idle machine in the time when the ma-
insurance premium
energy costs
spare parts inventory
investment interest rate
NOTES
maintenance investments
variable operating costs
fixed operating costs
profit margin
injury costs
General economic data
environmental cost
penalty cost due to late delivery)
lost production during stoppage
cost of rework of defected items
maintenance Indirect costs
idle machine (depreciation)
outsourcing
overheads (tools, management, etc)
spare parts
man-hour
Maintenance Direct costs
chine is not producing due to failures, UPBFR, planned stoppages and short stoppages. Also considered as part of the potential savings are the economic losses due to poor quality products caused by maintenance deficiency and tied capital due to extra spare parts inventory. On average, the total potential saving approximated SEK 30 million (US$3 million) and was increasing, as shown in Fig. 5. A Pareto diagram for the elements of the total economic losses (potential savings) is shown in Fig. 6. We can see that the losses due to short stoppages represent the highest value, followed by planned stoppages, quality problems, failures and
B. Al-Najjar, I. Alsyouf / European Journal of Operational Research 157 (2004) 643–657 Maintenance Mechanical Direct Costs for PM2 16 14 12 10 8 6 4 2 0
MSEK
20 18
653
Pareto Diagram for the Average Values of Losses and their Causes 17.302
16 14
Maintenance Mechanical Direct Costs for PM2
1997 12.351
1998 13.893
1999 11.166
2000
14.522
M S E K
12 10
9.565
8 6 4 2
1.699
1.091
0.410
0
Fig. 3. Direct maintenance costs of mechanical components.
Fig. 6. Pareto diagram for the total losses elements.
MSEK
Total maintenance investments in PM2 0.800 0.700 0.600 0.500 0.400 0.300 0.200 0.100 0.000
General Maintenance investment in PM2 PM2 Maintenance investment in training "COMPETENCE"
1997
1998
1999
Average short stoppages (performance efficiency) losses ‘profit & fixed cost (FC)’ Average unavailability ‘recoverable profit & FC)’ losses due to planned stoppages Average quality losses (profit. FC. and variable cost (VC). Average unavailability losses ‘profit & FC’ due to failures and UPBFR Average tied up capital costs due spare parts inventory
2000
Year
Fig. 4. Total investments in maintenance.
UPBFR and, finally, the tied capital due to the extra spare parts inventory which was calculated with respect to the year 1997. The maintenance department of the company has been implementing VBM for several years. Therefore, their long experience and competence in VBM enabled them to achieve a high technical efficiency and precision. For example, the average number of failures was only one per year, with an
average time of about 1.6 hours. Furthermore, the average number of UPBFRs was approximately 3.25 per year, with an average time of about 4.07 hours per stop. Moreover, they managed to integrate VBM with the production schedule. According to the production schedule, the paper machine was stopped every other week for an average of around eight hours for technical production reasons. The maintenance department therefore planned and performed an average of 12 replacements of rolling element bearings per year based on VBM recommendations in the time window initiated by the production department. Consequently, the minimum saving achieved by performing these maintenance tasks was estimated to be on average approximately SEK 4 million (US$0.4 million). As shown in Fig. 7, these savings were increasing in 1999 and 2000. The last factor is maintenance profit, which represents the difference between the minimum savings and maintenance
Potential savings (Total losses) 37.8
40.0 32.0
35.0
31.9
MSEK
30.0 25.0 20.0
18.5
15.0 10.0 5.0 0.0 1997
1998
1999
2000
year
Fig. 5. Total potential savings (economic losses).
Fig. 7. Minimum savings due to more efficient maintenance.
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investments: on average it was around SEK 3.58 million (US$0.358 million).
Total losses(profit+resources) per ton of paper produced (SEK/ton) 250
6.3. Performance measures SEK/ton
Twelve maintenance performance measures were developed and used. The first performance measure is the direct mechanical maintenance cost, i.e. the maintenance cost of the mechanical components that were maintained by VBM. The second performance measure is the total maintenance investment, i.e. the yearly investment spent on improving the competence and the systems of maintenance function. Both the first and second performance measures were shown in Figs. 3 and 4 respectively. The third, fourth and fifth measures are the ratio of the direct mechanical maintenance costs to operation cost, running time and passed (i.e. by quality control) product, which showed approximately the same trend (almost constant) during 1997–2000, as illustrated in Fig. 8. The sixth measure, shown in Fig. 9, is the total economic losses (in profit and resources) per ton of paper produced with accepted quality. It shows that on average approximately SEK 168 were lost for each ton of paper, and also the trend of losses increased. The seventh measure is the minimum savings divided by the tons of paper produced with accepted quality. The eighth measure is the ratio of maintenance investments to potential savings. It was appreciably small and varied between 1% and 2.2%. The ninth measure is the ratio of minimum
200 150 100 50 0 1997
1998
1999
2000
Year
Fig. 9. Total losses per ton of paper produced with accepted quality.
savings to total maintenance investments, shown in Fig. 10. On average it was around 9.2, which can be considered very high in comparison with the range achieved and published internationally, i.e. 5–10, see for example Nicholls (1989). The tenth measure is the ratio of lost profit to actual profit. We noticed that on average a value of around 3.5% of the actual generated profit could have been gained if, ideally, all the failures, UPBFR and short stoppages had been avoided using an efficient maintenance policy. It should be noted that the unproduced quantities during the planned stoppage time are not included. The eleventh measure is the restricted overall process effectiveness (ROPE). ROPE is equivalent to the OEE but restricted to when the machine is subject to mechanical faults that can be maintained by VBM. Finally, the last measure repre-
Ratio of minimum savings to maintenance investment 14.00 12.00 10.00 8.00 6.00 4.00 2.00 0.00 1997
1998
1999
2000
Year
Fig. 8. Maintenance mechanical direct cost to total running time.
Fig. 10. Minimum savings to total maintenance investment.
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655
sents the value of ROPE, divided by the direct mechanical maintenance costs.
These results are essential to achieve cost-effective continual improvement.
6.4. Benefits of collecting and treating company data in this way
7. Conclusions
Using the data collected in the technical and economic parts of the developed datasheet allowed us to achieve completely different results compared to those achieved by the company using their own information parameters. The benefits of applying the model and its new datasheet were described in Section 5.1. The results that are usually achieved based on the available databases are summarised below: 1. Frequency and duration of total stoppage time classified according to its different types, such as planned, unplanned and short stoppages. 2. Total poor quality quantities. 3. General economic data such as those used in annual reports, e.g. balance sheet, profit and loss statements. Using the current databases (directly), it is not possible to obtain detailed estimates of the economic consequences of the various production stoppages, poor quality and other cost factors such as tied capital in spare parts inventory. Furthermore, it is impossible to obtain the detailed elements of each stoppage time. Additionally, it is not straightforward to find detailed information about investments made, for example in the maintenance department, since they are registered as expenses in different accounts. This means that the company lacks the opportunity to achieve results such as: 1. Estimating and prioritising the various types of savings, e.g. as economic losses that could be achieved partially or completely by implementing a more efficient maintenance policy. 2. Identifying and tracing the real causes of the production losses, knowing how much and where investment should be allocated, and whether it is cost effective. 3. Obtaining the data required to monitor and control the performance of the maintenance and manufacturing process.
Using the model means that LCC factors will be used as monitoring parameters to provide the required information for decision-making, to ensure cost-effective actions and enhance continual improvement efforts cost-effectively. Applying this model establishes continual improvement as the driving force for more accurate and precise results. Comparing the minimum savings with the investments made for improving maintenance policy reveals how cost-effective the investments in maintenance were and whether or not they were relevant. Applying relevant performance measures helps to detect deviations at an early stage to avoid further economic losses. Finally, in a recession greater investment should be made in maintenance rather than reducing its budget, because investing in maintenance can return nine times the invested capital over the depreciation period. Acknowledgements This paper was one of the results of a project that was financially supported by the Swedish National Board for Industrial and Technical Development, NUTEK, and the Swedish companies StoraEnso Hylte AB, Volvo Truck Components AB in K€ oping, SKF Condition Monitoring, and ABB Alstom Power AB in V€axj€ o. We would like to thank the maintenance department staff at StoraEnso Hylte AB, in particular Mirela Jasarevic, J€ orgen Blomqvist, Bernt Petersson and Jan Andersen. Also, we would like to thank the centre of industrial competitiveness (CIC) at V€axj€ o University for their financial support. References Ahlmann, H., 1984. Maintenance effectiveness and economic models in the terotechnology concept. Maintenance Management International 4, 131–139.
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