- Email: [email protected]
Industrial Management in the Process Industry
Copyright ~ IFAC Information Control in Manufacturing, Nancy - Metz, France, 1998
INDUSTRIAL MANAGEMENT IN THE PROCESS INDUSTRY
Andre Thomas, Samir Lamouri
ENSGSI - 8, Rue Bastien Lepage - 54000 - NANCY. Ti!. 03.83.19.32.32 - Fax. 03.83.19.32.00 - E-Mail [email protected]. Proconseil Consulting Group Paris et Dipartement Organisation et Gestion de Production de l'Universite de Cergy-Pontoise.
Abstract : The analysis of the differences between production management in process flow and discreet flow industries shows that this differences exist essentially in short and very short terms. The functions in middle and long terms of discreet flow MRP2 systems are usefull in process flow industry. Concerning quality and just in time, we observed that the" tools" are the same and focus of the improvment of non-production because the resulting costs. Copyright © 1998 IFAC Keywords : Process industry, production management, just in time.
The definition in the APICS 1 dictionary concerning "the process industry" is: Process industries are production systems that adds value by mixing, separating, forming and/or performing chemical reactions, etc.. These processes can be either continuous, or batched, and, normally, require specific fixed management and large investments.
1. INTRODUCTION Persons taking an interest in industrial management wonder often about what it happens in this area in process industries, it means, in the entreprises whose material flows are told "continuous". We wanted in this article, without having the pretentiousness to be exhaustive neither to present the whole so human that financiers particularities of these two kinds of entreprises, to show the current differences between ways of management of production of this type of flow as compared to discrete flows.
Typical examples of process industries are the chemical industry, the oil yielding industry, the manufacture of paper and the complete agricultural processing or pharmaceutical sector. In a chemical industry plant, materials can be formed in several successive steps, such as separation, reaction and packaging.
2. WHAT IS PROCESS MANUFACTURING? Process manufacturing systems are characterised by large investments in equipment, "inflexible" production lines, that is fixed process sheets, large production volumes and large finished product volumes (Hill, 1989).
As for the brewing process, it includes the following phases: acceptance-storage of raw materials, brewing, fermentation/storage, filteringlstabilisation, packaging. A pharmaceutical industry process can include: acceptance of raw materials, inspection,
1
841
American Production and Inventory Control Society.
quarantine, storage, weighing, mIxIng, forming, packaging, quarantine, inspection. The managers, in these types of companies, use process flow charts to describe how their products are made unlike managers in the manufacturing industry who use process sheets for each article of each bill of materials. These can be represented in the "product process" matrix of Hayes and Wheelwright - (Fig. 1) :
3. INDUSTRIAL MANAGEMENT IN THE PROCESS INDUSTRY The most commonly used system in the manufacturing industry is MRP2 (Manufacturing Resources Planning - We esteem that 60 to 70o/c of companies have such an industrial management system). What is the situation in the process industry? Before replying to this question, we must draw up an inventory of the differences which exist between the two types of manufacture (Hill, 1989, Thomas et aI., 1995 and Thomas et aI., 1996-Table 1): There are four main families of criteria in this table: Relation to market Production process Quality Management and planning. We can therefore see that in the process industry, the automation of the production process is highly developed whereas, in the manufacturing industry, the management and planning system is more sophisticated. Thus, to reply to the question posed initially at the beginning of this chapter, we can say that the highest level MRP2 functions are used in the process flow industries. We will analyse these systems in more detail in the following chapters.
Fig.l The product-Process matrix It is possible to propose a typology of the process industries by categorising them according to types of products. Koene proposes 9 classes (Koene, 1988): Food, Paper and cardboard, Chemistry, Oil, Rubber and plastics, Construction materials, Pottery and glassware, Iron and steel industry, Energy. In particular, it seems interesting to classify the chemical industries on the basis of their categories of products and also from their process structures. Indeed, the process structure plays an important role in defining production planning problems and these are normally categorised into "single-step processes" and "multi-step processes" which again can be subdivided into "single line process" or "parallel lines" depending on whether the lines are dedicated to one product or not (Fig. 2). It is possible to push the classification still further: continuous/semicontinuous, with or without intermediary storage (tanks, reservoirs, etc.), size limited or not, importance of the production mix, etc..
4. INDUSTRIAL MANAGEMENT SYSTEMS IN THE PROCESS INDUSTRY In general, an industrial management system is more than a production management system as it helps in optimising production and in improving the flexibility and the reaction capability by acting, not only on the productive system resources, but on all the resources of the company and this by using the maximum time and date scale. That is, it processes information and decisions which may be operational (and concerning the short term), tactical (medium term) or strategic (long tenn) (today, we speak of enterprise resource planning). Melnik and Narasimhan (Melnik et aI., 1992) propose a description and compare it with the CIM (Computer Integrated Manufacturing) concept: "The integration of computer-assisted production operations and processes manage the functions optimum required for productive use and development of the management and manufacturing resources required to reach strategic targets" . Ashayeri and Selen (Ashayeri et aI., 1996) propose a certain number of functionalities specific to this process mode:
4.1. Operational level
At this level, the main functionalities are related to data acquisition. This consists in retrieving, via sensors and other automatic equipment, information
842
which will allow an indicator system to live (production rate, % of non-production time, etc.), which will provide input for the production management data base for scheduling decisions (material stock level in tank, in process, etc.) and for
the tracability of the batches and the follow up of production outputs or for the cost analysis department to detennine operating costs (volume of fuel consumed, number of Kw of electricity, etc.).
Process industries Relations with market Type of products Product assortment Demand per product Cost per product Winning advantages Transport costs New products Production process Process sheets Layout Flexibility Production equipment Labour value Capital value Change time In-progress Volumes Quality Environmental constraints Danger Quality measurement Planning and management Production Long-term planning Short-term planning Planning of launchings Material flow Qutput variability Management syst.breakdown Co-products Batch traceability
Discrete flow industries
Standard Small Large Low Price, deli very guarantee High Few
Customised Large Small High Delivery speed, prod. charact. Low Many
Fixed Per products Low Specialised Low High High Low High
Variable with substitute Per fucntion (changes) High All-purpose High Low (changes) Low High (changes) Low
Yes Sometimes Sometimes long (pharma)
Rarely Almost never Short
On stock Capacity Use of capacity Availability of capacity Divergent + convergent Sometimes high Via formulas Sometimes Often required
On order Product design Use of personnel Availability of material Convergent Often low Via bills of materials None Sometimes unnecessary
Table 1 Differences between process industries and discrete flow industries deadlines. It must also ensure follow-up of production commitments faced with capacity target trends to allow real-time information on real and/or target delivery dates (in relation to requirement dates). • Scheduling software packages which generate programmes or reschedulings by hierarchically structuring and minimising the campaign setup times. They must be built according to a constraint-oriented management logic and propose finite capacity schedulings for, as we will see for the master production schedule, in the process industry, it is the capacity of the work centers which controls the load (Ashayeri et aI., 1996); these software packages can propose schedulings detennined by mathematical calculations as a function of priority rules, by heuristics or by using dynamic flow simulation. • Maintenance software packages which must be related to the master production schedule (MPS) software packages because of capacity reservations for maintenance operations. • Master production schedule software packages (MPS - often called production plan by error). They
It is interesting to see that, at this level, quality control and management software packages can be integrated by the fact that the quality control operations are themselves integrated into the process operations (Thomas et aI., 1996). They comprise a real process sheet operation. Also, SPC 2 type software packages and those required for documentary management must be interfaced with the general management system.
4.2. Tactical level At the tactical level, the industrial management system must guarantee efficient use of the production equipment faced with finn and planned orders. This leads to the use of "conventional" production management software packages, that is: • Order launching software allowing recompletion of stocks required to deliver customer orders within
2
Statistical Process Control
843
means are rare and costly) because of the sub- and co-product notions (that we only know after the event!), because of the output variability, the variability in ways of proceeding (replacement recipes), the multitude of measurement units, and because of batch follow-up and traceability (Thomas et aI., 1996). To make progress with the description of industrial management in the process industry, we will show the impact only on the infrastructure in the implementation of scheduling and a just-in-time policy.
must take into account the fact that the capacities must be programmed before the materials are ordered (capacity driver planning). They use mix recipes rather than bills of materials but overall operate in the same as in the manufacturing industry. There are many complex links between these "recipes" on account of the "co-products" and the "sub-products" and also on account of the degrees of quality of the materials used and the factors influencing the process. The temperature and the pressure induce, for example, different quality levels at process output and, therefore, the MPS software packages must be capable of taking into account the fact that a derived product, a sub-product, can be manufactured instead of the one that was planned.
5. PROCESS FLOW SCHEDULING (PFS) The basic principles of PFS are:
4.3. Strategical level
5.1. The calculations are based on the structure of the process.
At business plan (BP) and production plan (PP) level, the differences are no longer perceptible (Thomas et aI., 1995). The BPs are broken down into budgets and the integration of predictions is also made via the PPs and MPSs as in the manufacturing industry. MRP2 standard software packages are in fact difficult to use as such because of the specificity of the flow industry: the large capacity of the work stations (the
The scheduling programmes are generated by calculations based on the structure of the process and not, as with discrete flows MRP, on the bills of materials. Figures 3 and 4 show several examples of process structures:
Fig.3 Process structure-Example FigA Process structure-Brewery From (Taylor et aI., 1996) and (Thomas et aI., 1995) unit as they will be used, and therefore programmed, as a given entity. However, each process unit will have its own programme and each programme must concern one unit. A process group includes one or more units grouped together for scheduling purposes. Each of these units will have its own programme but these will be related (synchronised) by a certain number of constraints. For example, in figure 5, the mix unit generates blue, red and green products and, in a process without stocks (there are no intermediary
Process flow scheduling often uses specific terminology. Figure 3, for example, shows a process structure which consists of three production units. These units are structured into two groups in which we can identify several process steps thanks to different stocks (figure 5). A process unit is a set of equipment participating in a given programme; this equipment is therefore programmed at the same time. Thus, a set of heat exchangers, a reactor and the distillation towers can be part of the same process
844
stocks between the mixer and packaging), these three sort of products will be packaged into small and large containers. The mix and packaging programmes must therefore be synchronised.
5.2. Group scheduling techniques • Process-oriented programming: in many companies, group capacity limits are clearly defined and in fact, as shown on figure 6, a finite capacity scheduling must be proposed for these groups. • Material-oriented programming follows the same logic as MRP2 and develops a material planning and controls the corresponding capacities of the processes. The difference which exist with discrete flows consists in that, for the latter, we generate a material planning and, then, check the fact that the capacities are adequate (first the infinite capacity then the finite capacity). With process flow programming, the material will only be planned if the capacity is ensured (the capacity therefore takes priority).
5.3. Scheduling techniques for a complete group • Backward programming - This procedure is very often used. The manager positions the last steps in the process first on the time diagram and successively works back to the first ones. This is a "customercentred" procedure which corresponds to the "adjustment at latest stage" of MRP2. • Forward programming - This is less used. It corresponds to the "adjustment at earliest stage" and is the exact opposite of the previous procedure. This type of programming is interesting in all cases where it is the raw material which conditions the execution of a programme. This is the case in the food industry: if the climate leads to a IS-day delay in the harvesting of sugar beets, the sugar production process will bear the consequences. • The third type corresponds to the application of constraint-oriented management (CaM) rules. We thus start by programming the capacity constraint and, upstream and downstream of the process, we apply backward and forward programming.
Fig.5 Process structure-Example A process step consists of groups and/or units located between two intennediary storage points. Thus, between the raw material stocks and the intermediary stocks, the reactor also comprises a process step. And lastly, the complete process is a set of steps that can be programmed quite independently from the other processes in the company. We can therefore see that to implement scheduling it would be absurd to generate programmes for each process unit. One must, as in a conventional constraint-oriented management (CaM) logic, programme the capacity constraint process groups first and then deduce the rest from the other programmes of all groups and all steps of the process concerned. Faced with these constraints, the programme evaluation indicators may be the stock level (the most important probably), the leadtimes, material output, resulting load rate, etc. (figure 6).
~
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'~
01
Scheduling stock Indicator
We use "just-in-time" here in the sense given by Sandras (1989) and APICS in its dictionary, that is: The elimination of waste and continued improvement of productivity in the execution of all manufacturing activities required to produce the final product. Many lIT philosophy aspects, such as improving quality, reducing stocks, participative management and the elimination of waste, can be applied in the same way to process industries and to manufacturing industries (Hall, 1992). However, in a process environment, the progress proposed subsequent to actions under a lIT project will more specifically concern the non-production activities, such as material transfer and storage, due to the infrastructure itself (the equipment being what it is, it is hardly
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6. "lUST IN TIME" (lIT) IN PROCESS FLOW SCHEDULING
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Fig.6 Scheduling stock indicator
845
possible to implement, without inducing extremely high costs, transformations concerning a process unit). This consists then in acting on the organisation to eliminate excess stocks, wait times or to reduce leadtimes, handling operations, transport, etc.. For this, the ways of proceeding and implementation methods in no way differ from that which is commonly done in other companies and for other flow types(Cook et aI.,1996; Billesbach, 1994). It may however be useful to call on less used types of quality tools "judged as classical", such as the causeeffect diagram and the ABC analysis. As an example, we will briefly cite the case of the improvement of a bottling process in a brewery (Thomas et aI., 1994). The method tools used were the process cause-effect diagram and a "bill of materials" of the ABC diagram. The problem consisted in eliminating neck chips, detected during capping, on a bottling line. The technique consisted in describing the complete process and in analysing step by step all causes which could lead to chipping (figure 7).
7. CONCLUSION To conclude, it seems that the industrial management modes, between discrete flow industries and process flow industries, diverge less than is often believed. The greatest differences lie in the most operational management levels; these are those which concern the short terms. The main cause is the nature of the process itself and its equipment. This therefore induces a complete management logic which is more "capacity centred" (on account of the operating costs) than "material centred" as in the conventional MRP2 of the manufacturing industry.
REFERENCES Ashayeri et Selen (1996). Computer intergrated manufacturing in the chemical industry, in Production and inventory management journal, Vo1.37 pp 52-58. Billesbach T. (1994) Applying lean production principles to a process facility in Production and inventory management journal Vo1.35, pp40-45. Chatillon et Thomas (1995), Analyse des ecarts entre systemes de GP caracterisant les processus semicontinus et les systemes propres a 1'industrie manufacturiere, DEA de A. Chatillon ENSGSI de I'INPL. Cook and Rogowski (1996), Applying JIT principles to Continuous Process Manufacturing Supply Chains in Production and inventory management journal, Vol. 37 ppI2-18. Florentiny et Thomas (1996), Modelisation d'un systeme productif en entreprise pharmaceutique, DEA de D. Florentiny ENSGSI de 1'INPL. Hall R., (1992), Just in time certification reviaw course student guide, APICS. Hayes-Wheelwright, (1979), Link manufacturing process and product life cycles, Harvard business review, January-February, pp 34-39 Hill, (1989), Manufacturing strategy, Irwin Business. Koene, (1988), Logistiek in de processindustrie, Tijdschrift voor inkoop en logistiek, n° 12, pp 1217 Leonard. et Thomas, (1994), Demarche de resolution de problemes illustree par son application a une ligne d'embouteillage, DEA de F. Leonard ENSGSI de I'INPL. Melnik et Narasimhan, (1992), Computer integrated manufacturing, guidelines and applications from industrial leaders, Business One Irwin. Sandras, Jr, (1989), Just in time: making it happen, Oliver Wright ed. Taylor and Steven F. Bolander (1996), Can process Flow Scheduling help you? in APICS, The performance advantage, pp 44-50.
Fig.7 Process Cause-Effect Diagram This analysis was conducted for each step in the process. It allowed us to list, on the one hand, the causes related to the process on the process unit and, in the other hand, the causes related to the materials. By a series of hierarchically-structured ABC analyses (figure 8), the main causes were evidenced. Thus certain causes could be eliminated thanks to proposals for improvement, others gave rise to experimental plans with the aim of optimising the steps concerned in the process to make it more "robust" . ~
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Fig. 8 ABC analysis hierarchical structuring
846
INDUSTRIAL MANAGEMENT IN THE PROCESS INDUSTRY
Andre Thomas, Samir Lamouri
ENSGSI - 8, Rue Bastien Lepage - 54000 - NANCY. Ti!. 03.83.19.32.32 - Fax. 03.83.19.32.00 - E-Mail [email protected]. Proconseil Consulting Group Paris et Dipartement Organisation et Gestion de Production de l'Universite de Cergy-Pontoise.
Abstract : The analysis of the differences between production management in process flow and discreet flow industries shows that this differences exist essentially in short and very short terms. The functions in middle and long terms of discreet flow MRP2 systems are usefull in process flow industry. Concerning quality and just in time, we observed that the" tools" are the same and focus of the improvment of non-production because the resulting costs. Copyright © 1998 IFAC Keywords : Process industry, production management, just in time.
The definition in the APICS 1 dictionary concerning "the process industry" is: Process industries are production systems that adds value by mixing, separating, forming and/or performing chemical reactions, etc.. These processes can be either continuous, or batched, and, normally, require specific fixed management and large investments.
1. INTRODUCTION Persons taking an interest in industrial management wonder often about what it happens in this area in process industries, it means, in the entreprises whose material flows are told "continuous". We wanted in this article, without having the pretentiousness to be exhaustive neither to present the whole so human that financiers particularities of these two kinds of entreprises, to show the current differences between ways of management of production of this type of flow as compared to discrete flows.
Typical examples of process industries are the chemical industry, the oil yielding industry, the manufacture of paper and the complete agricultural processing or pharmaceutical sector. In a chemical industry plant, materials can be formed in several successive steps, such as separation, reaction and packaging.
2. WHAT IS PROCESS MANUFACTURING? Process manufacturing systems are characterised by large investments in equipment, "inflexible" production lines, that is fixed process sheets, large production volumes and large finished product volumes (Hill, 1989).
As for the brewing process, it includes the following phases: acceptance-storage of raw materials, brewing, fermentation/storage, filteringlstabilisation, packaging. A pharmaceutical industry process can include: acceptance of raw materials, inspection,
1
841
American Production and Inventory Control Society.
quarantine, storage, weighing, mIxIng, forming, packaging, quarantine, inspection. The managers, in these types of companies, use process flow charts to describe how their products are made unlike managers in the manufacturing industry who use process sheets for each article of each bill of materials. These can be represented in the "product process" matrix of Hayes and Wheelwright - (Fig. 1) :
3. INDUSTRIAL MANAGEMENT IN THE PROCESS INDUSTRY The most commonly used system in the manufacturing industry is MRP2 (Manufacturing Resources Planning - We esteem that 60 to 70o/c of companies have such an industrial management system). What is the situation in the process industry? Before replying to this question, we must draw up an inventory of the differences which exist between the two types of manufacture (Hill, 1989, Thomas et aI., 1995 and Thomas et aI., 1996-Table 1): There are four main families of criteria in this table: Relation to market Production process Quality Management and planning. We can therefore see that in the process industry, the automation of the production process is highly developed whereas, in the manufacturing industry, the management and planning system is more sophisticated. Thus, to reply to the question posed initially at the beginning of this chapter, we can say that the highest level MRP2 functions are used in the process flow industries. We will analyse these systems in more detail in the following chapters.
Fig.l The product-Process matrix It is possible to propose a typology of the process industries by categorising them according to types of products. Koene proposes 9 classes (Koene, 1988): Food, Paper and cardboard, Chemistry, Oil, Rubber and plastics, Construction materials, Pottery and glassware, Iron and steel industry, Energy. In particular, it seems interesting to classify the chemical industries on the basis of their categories of products and also from their process structures. Indeed, the process structure plays an important role in defining production planning problems and these are normally categorised into "single-step processes" and "multi-step processes" which again can be subdivided into "single line process" or "parallel lines" depending on whether the lines are dedicated to one product or not (Fig. 2). It is possible to push the classification still further: continuous/semicontinuous, with or without intermediary storage (tanks, reservoirs, etc.), size limited or not, importance of the production mix, etc..
4. INDUSTRIAL MANAGEMENT SYSTEMS IN THE PROCESS INDUSTRY In general, an industrial management system is more than a production management system as it helps in optimising production and in improving the flexibility and the reaction capability by acting, not only on the productive system resources, but on all the resources of the company and this by using the maximum time and date scale. That is, it processes information and decisions which may be operational (and concerning the short term), tactical (medium term) or strategic (long tenn) (today, we speak of enterprise resource planning). Melnik and Narasimhan (Melnik et aI., 1992) propose a description and compare it with the CIM (Computer Integrated Manufacturing) concept: "The integration of computer-assisted production operations and processes manage the functions optimum required for productive use and development of the management and manufacturing resources required to reach strategic targets" . Ashayeri and Selen (Ashayeri et aI., 1996) propose a certain number of functionalities specific to this process mode:
4.1. Operational level
At this level, the main functionalities are related to data acquisition. This consists in retrieving, via sensors and other automatic equipment, information
842
which will allow an indicator system to live (production rate, % of non-production time, etc.), which will provide input for the production management data base for scheduling decisions (material stock level in tank, in process, etc.) and for
the tracability of the batches and the follow up of production outputs or for the cost analysis department to detennine operating costs (volume of fuel consumed, number of Kw of electricity, etc.).
Process industries Relations with market Type of products Product assortment Demand per product Cost per product Winning advantages Transport costs New products Production process Process sheets Layout Flexibility Production equipment Labour value Capital value Change time In-progress Volumes Quality Environmental constraints Danger Quality measurement Planning and management Production Long-term planning Short-term planning Planning of launchings Material flow Qutput variability Management syst.breakdown Co-products Batch traceability
Discrete flow industries
Standard Small Large Low Price, deli very guarantee High Few
Customised Large Small High Delivery speed, prod. charact. Low Many
Fixed Per products Low Specialised Low High High Low High
Variable with substitute Per fucntion (changes) High All-purpose High Low (changes) Low High (changes) Low
Yes Sometimes Sometimes long (pharma)
Rarely Almost never Short
On stock Capacity Use of capacity Availability of capacity Divergent + convergent Sometimes high Via formulas Sometimes Often required
On order Product design Use of personnel Availability of material Convergent Often low Via bills of materials None Sometimes unnecessary
Table 1 Differences between process industries and discrete flow industries deadlines. It must also ensure follow-up of production commitments faced with capacity target trends to allow real-time information on real and/or target delivery dates (in relation to requirement dates). • Scheduling software packages which generate programmes or reschedulings by hierarchically structuring and minimising the campaign setup times. They must be built according to a constraint-oriented management logic and propose finite capacity schedulings for, as we will see for the master production schedule, in the process industry, it is the capacity of the work centers which controls the load (Ashayeri et aI., 1996); these software packages can propose schedulings detennined by mathematical calculations as a function of priority rules, by heuristics or by using dynamic flow simulation. • Maintenance software packages which must be related to the master production schedule (MPS) software packages because of capacity reservations for maintenance operations. • Master production schedule software packages (MPS - often called production plan by error). They
It is interesting to see that, at this level, quality control and management software packages can be integrated by the fact that the quality control operations are themselves integrated into the process operations (Thomas et aI., 1996). They comprise a real process sheet operation. Also, SPC 2 type software packages and those required for documentary management must be interfaced with the general management system.
4.2. Tactical level At the tactical level, the industrial management system must guarantee efficient use of the production equipment faced with finn and planned orders. This leads to the use of "conventional" production management software packages, that is: • Order launching software allowing recompletion of stocks required to deliver customer orders within
2
Statistical Process Control
843
means are rare and costly) because of the sub- and co-product notions (that we only know after the event!), because of the output variability, the variability in ways of proceeding (replacement recipes), the multitude of measurement units, and because of batch follow-up and traceability (Thomas et aI., 1996). To make progress with the description of industrial management in the process industry, we will show the impact only on the infrastructure in the implementation of scheduling and a just-in-time policy.
must take into account the fact that the capacities must be programmed before the materials are ordered (capacity driver planning). They use mix recipes rather than bills of materials but overall operate in the same as in the manufacturing industry. There are many complex links between these "recipes" on account of the "co-products" and the "sub-products" and also on account of the degrees of quality of the materials used and the factors influencing the process. The temperature and the pressure induce, for example, different quality levels at process output and, therefore, the MPS software packages must be capable of taking into account the fact that a derived product, a sub-product, can be manufactured instead of the one that was planned.
5. PROCESS FLOW SCHEDULING (PFS) The basic principles of PFS are:
4.3. Strategical level
5.1. The calculations are based on the structure of the process.
At business plan (BP) and production plan (PP) level, the differences are no longer perceptible (Thomas et aI., 1995). The BPs are broken down into budgets and the integration of predictions is also made via the PPs and MPSs as in the manufacturing industry. MRP2 standard software packages are in fact difficult to use as such because of the specificity of the flow industry: the large capacity of the work stations (the
The scheduling programmes are generated by calculations based on the structure of the process and not, as with discrete flows MRP, on the bills of materials. Figures 3 and 4 show several examples of process structures:
Fig.3 Process structure-Example FigA Process structure-Brewery From (Taylor et aI., 1996) and (Thomas et aI., 1995) unit as they will be used, and therefore programmed, as a given entity. However, each process unit will have its own programme and each programme must concern one unit. A process group includes one or more units grouped together for scheduling purposes. Each of these units will have its own programme but these will be related (synchronised) by a certain number of constraints. For example, in figure 5, the mix unit generates blue, red and green products and, in a process without stocks (there are no intermediary
Process flow scheduling often uses specific terminology. Figure 3, for example, shows a process structure which consists of three production units. These units are structured into two groups in which we can identify several process steps thanks to different stocks (figure 5). A process unit is a set of equipment participating in a given programme; this equipment is therefore programmed at the same time. Thus, a set of heat exchangers, a reactor and the distillation towers can be part of the same process
844
stocks between the mixer and packaging), these three sort of products will be packaged into small and large containers. The mix and packaging programmes must therefore be synchronised.
5.2. Group scheduling techniques • Process-oriented programming: in many companies, group capacity limits are clearly defined and in fact, as shown on figure 6, a finite capacity scheduling must be proposed for these groups. • Material-oriented programming follows the same logic as MRP2 and develops a material planning and controls the corresponding capacities of the processes. The difference which exist with discrete flows consists in that, for the latter, we generate a material planning and, then, check the fact that the capacities are adequate (first the infinite capacity then the finite capacity). With process flow programming, the material will only be planned if the capacity is ensured (the capacity therefore takes priority).
5.3. Scheduling techniques for a complete group • Backward programming - This procedure is very often used. The manager positions the last steps in the process first on the time diagram and successively works back to the first ones. This is a "customercentred" procedure which corresponds to the "adjustment at latest stage" of MRP2. • Forward programming - This is less used. It corresponds to the "adjustment at earliest stage" and is the exact opposite of the previous procedure. This type of programming is interesting in all cases where it is the raw material which conditions the execution of a programme. This is the case in the food industry: if the climate leads to a IS-day delay in the harvesting of sugar beets, the sugar production process will bear the consequences. • The third type corresponds to the application of constraint-oriented management (CaM) rules. We thus start by programming the capacity constraint and, upstream and downstream of the process, we apply backward and forward programming.
Fig.5 Process structure-Example A process step consists of groups and/or units located between two intennediary storage points. Thus, between the raw material stocks and the intermediary stocks, the reactor also comprises a process step. And lastly, the complete process is a set of steps that can be programmed quite independently from the other processes in the company. We can therefore see that to implement scheduling it would be absurd to generate programmes for each process unit. One must, as in a conventional constraint-oriented management (CaM) logic, programme the capacity constraint process groups first and then deduce the rest from the other programmes of all groups and all steps of the process concerned. Faced with these constraints, the programme evaluation indicators may be the stock level (the most important probably), the leadtimes, material output, resulting load rate, etc. (figure 6).
~
li§ j
'~
01
Scheduling stock Indicator
We use "just-in-time" here in the sense given by Sandras (1989) and APICS in its dictionary, that is: The elimination of waste and continued improvement of productivity in the execution of all manufacturing activities required to produce the final product. Many lIT philosophy aspects, such as improving quality, reducing stocks, participative management and the elimination of waste, can be applied in the same way to process industries and to manufacturing industries (Hall, 1992). However, in a process environment, the progress proposed subsequent to actions under a lIT project will more specifically concern the non-production activities, such as material transfer and storage, due to the infrastructure itself (the equipment being what it is, it is hardly
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~~
~
~~
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6. "lUST IN TIME" (lIT) IN PROCESS FLOW SCHEDULING
-> TIme
I
FIgure 6
~ ~
~///////////////////////////////////////////////////////////////////////////////////////////////~
Fig.6 Scheduling stock indicator
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possible to implement, without inducing extremely high costs, transformations concerning a process unit). This consists then in acting on the organisation to eliminate excess stocks, wait times or to reduce leadtimes, handling operations, transport, etc.. For this, the ways of proceeding and implementation methods in no way differ from that which is commonly done in other companies and for other flow types(Cook et aI.,1996; Billesbach, 1994). It may however be useful to call on less used types of quality tools "judged as classical", such as the causeeffect diagram and the ABC analysis. As an example, we will briefly cite the case of the improvement of a bottling process in a brewery (Thomas et aI., 1994). The method tools used were the process cause-effect diagram and a "bill of materials" of the ABC diagram. The problem consisted in eliminating neck chips, detected during capping, on a bottling line. The technique consisted in describing the complete process and in analysing step by step all causes which could lead to chipping (figure 7).
7. CONCLUSION To conclude, it seems that the industrial management modes, between discrete flow industries and process flow industries, diverge less than is often believed. The greatest differences lie in the most operational management levels; these are those which concern the short terms. The main cause is the nature of the process itself and its equipment. This therefore induces a complete management logic which is more "capacity centred" (on account of the operating costs) than "material centred" as in the conventional MRP2 of the manufacturing industry.
REFERENCES Ashayeri et Selen (1996). Computer intergrated manufacturing in the chemical industry, in Production and inventory management journal, Vo1.37 pp 52-58. Billesbach T. (1994) Applying lean production principles to a process facility in Production and inventory management journal Vo1.35, pp40-45. Chatillon et Thomas (1995), Analyse des ecarts entre systemes de GP caracterisant les processus semicontinus et les systemes propres a 1'industrie manufacturiere, DEA de A. Chatillon ENSGSI de I'INPL. Cook and Rogowski (1996), Applying JIT principles to Continuous Process Manufacturing Supply Chains in Production and inventory management journal, Vol. 37 ppI2-18. Florentiny et Thomas (1996), Modelisation d'un systeme productif en entreprise pharmaceutique, DEA de D. Florentiny ENSGSI de 1'INPL. Hall R., (1992), Just in time certification reviaw course student guide, APICS. Hayes-Wheelwright, (1979), Link manufacturing process and product life cycles, Harvard business review, January-February, pp 34-39 Hill, (1989), Manufacturing strategy, Irwin Business. Koene, (1988), Logistiek in de processindustrie, Tijdschrift voor inkoop en logistiek, n° 12, pp 1217 Leonard. et Thomas, (1994), Demarche de resolution de problemes illustree par son application a une ligne d'embouteillage, DEA de F. Leonard ENSGSI de I'INPL. Melnik et Narasimhan, (1992), Computer integrated manufacturing, guidelines and applications from industrial leaders, Business One Irwin. Sandras, Jr, (1989), Just in time: making it happen, Oliver Wright ed. Taylor and Steven F. Bolander (1996), Can process Flow Scheduling help you? in APICS, The performance advantage, pp 44-50.
Fig.7 Process Cause-Effect Diagram This analysis was conducted for each step in the process. It allowed us to list, on the one hand, the causes related to the process on the process unit and, in the other hand, the causes related to the materials. By a series of hierarchically-structured ABC analyses (figure 8), the main causes were evidenced. Thus certain causes could be eliminated thanks to proposals for improvement, others gave rise to experimental plans with the aim of optimising the steps concerned in the process to make it more "robust" . ~
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Fig. 8 ABC analysis hierarchical structuring
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