Production planning and control—The tool to ensure logistical quality

Robotics & Computer-Integrated Manufacturing, Vol. 10, No. 1/2, pp. 99 107, 1993

0736 5845/93 $5.00 + 0.00 @ 1992 Pergamon Press Ltd

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Paper P R O D U C T I O N P L A N N I N G A N D C O N T R O L - - T H E TOOL TO ENSURE LOGISTICAL QUALITY HANS-PETER WIENDAHL University of Hannover, Germany

In addition to the technical quality of their products, companies concentrate increasingly on the quality of their logistics. Delivery time and due date performance are the external, utilization and inventory the internal logistical quality features. Conventional MRP systems do not measure these objectives and therefore do not solve conflicts between targets. With the funnel model and throughput diagram a new approach was developed to ensure a closed loop between planning and control of quality features. After a short description of the theory, the three components of the quality assurance system will be illustrated. A monitoring system measures continuously the logistical targets, supported by a new type of graphics. The planning system ensures sound values based on the company's production strategies. A knowledge-based diagnosis system detects deviations between scheduled and actual values, ascertains the causes and generates remedial measures. Increasingly, commercial software incorporates these new ideas. Some results derived by companies will finally illustrate the remarkable improvements achieved so far.

system is illustrated as a funnel with incoming and outgoing orders and orders-in-hand. On the righthand side, the input and output curves can be seen, illustrating the events in the funnel. The output curve is plotted by cumulatively entering the orders dispatched together with their work content assessed in scheduled hours according to the respective exit time point, commencing at the origin of the coordinates. The start of the input curve is determined by the initial inventory existing in the work system at the beginning of the reference period. From this basis, the input curve is developed by the same method as the output curve. Both curves together describe the flow of orders through the work system; this representation is therefore called the throughput diagram. The more accurate the record time points and the correspondence of scheduled times with actual times, the closer the diagram will be to reality. All capacity stages, from an individual workstation to a complete factory can be represented without any change in principle of its structure. The next important step in building the model consists of representing the four logistic targets in a throughput diagram of the work system. Figure 2 outlines this procedure in four identical throughput diagrams. Inventory can be calculated at any time from the vertical distance between input and output curve. The lead time of the orders in this workplace corresponds to the length of the throughput elements of each order "logged off". Described here as a throughput element of an order in a work system is

1. I N T R O D U C T I O N The guiding concepts of CIM (computer-integrated manufacturing), logistics and just-in-time production are today regarded as initial solutions for restructuring production industry. A central building block of all these concepts is production planning and control (PPC). It is nevertheless becoming increasingly clear that the previous working hypotheses and methods are no longer adequate, as they still place too much reliance on formerly more usual procedures. It is today far more necessary to describe production process and order throughput in a model which mathematically describes and clarifies the four central logistic targets of lead time, schedule observance, inventory and utilization and their inter-relationship.1 The following prerequisites are necessary for such a model: it must be possible to obtain the data necessary for construction of the model from the normal shop data, including in particular basic shop data and progress data. The model must also permit graphic representation of order throughput, i.e. it must be visualizable. Lastly, it must be capable of numerical description, and therefore suitable for computer application. After an explanation of the model, three fields of application are described. 2. T H E T H R O U G H P U T

DIAGRAM

Let us first of all look at a single work system. This may be a machine, a shop, or even a warehouse into which material is loaded and from which it is dispatched. On the left-hand side of Fig. 1 this work 99

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the square of lead time times work hours content. Because of the "swopping over" of orders which mostly takes place in the order queue in the workplace, the throughput elements are not located between the input and output curves. Utilization can be represented by superimposing the capacity curve on the output curve. Finally, schedule deviation can be visibly revealed by superimposing schedule due-times on actual due-times, in the present case for "loggedoff" orders. Areas to the left of the output curve indicate a delay; areas to the right of the output curve indicate too-early completion. Inputs can also be represented in the same graphical form. To date, the most common application of the throughput diagram is for the graphical representation of work and assembly places which are organized on the job shop principle. Figure 3, as a typical

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example, shows the diagram of a group of workstations with NC machines in a tool and precision engineering company over an investigation period of 16 weeks. The average (weighted) lead time of the 35 work operations logged off in this period of time was 23 working days; the unweighted figure was around 18 working days. [The difference between these two figures is due to the weighting (multiplication) of each lead time by the work content of the order concerned.] Sharp fluctuations can be seen in input and output trends, due to large differences in work content and timewise badly controlled input. Superimposed on this situation are frequent changes of sequence order, resulting in a wide dispersion of lead time. In contrast, the throughput diagram of a flexible manufacturing system consisting of four machining centers over a 2-day period is seen to be considerably more even (Fig. 4). 3 Processing of the individual workpieces gave rise to only very slight dispersion of implementation times, with at the same time a very low mean value. Inventory tie-up in the system is limited by the number of available workpiece pallets in the system, and finally, there were scarcely any changes of sequence in the system. Only breakdowns of individual machine tools led to deviations from ideal trend and consequently to losses of output. Overall, the performance of the system is characterized by short lead times with little variation and low inventories, with as a consequence, good schedule observance. Figure 5 shows the throughput diagram as a very universal tool to visualize the events of any kind of batch production. This diagram shows a design division of a computer manufacturer, equipped with several CAD systems. The CAD workstations are in use for routing circuit diagrams to design electronic components. The input and output curves are parallel so the system is balanced. The throughput elements show considerable sequence transpositions. Due to the fact

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Robotics & Computer-IntegratedManufacturing • Volume 10, Numbers 1/2. 1993 according to orders released. Finally, in the longterm, it is a question of whether capacities correspond to the constantly changing production program.

that in this case it is possible to interrupt the processing of orders with high order time, those with low order time were preferred. 3. A P P L I C A T I O N O F T H E T H R O U G H P U T DIAGRAM

For example, a commercial system which translates that into reality was realized as follows. The system is based on the extended funnel model of the batch production as shown in Fig. 7, illustrating the flow of orders through a job shop. 4'5 The model is divided into two sections "order stock", containing the

3.1. Monitoring It has always been possible to monitor production processes by means of regularly calculated characteristic figures. These were mostly defined according to the individual workshop and were mainly limited to production output, utilization and cost follow-up. As compared with this, the throughput diagram makes possible a general illustration of order flow and an intrinsically conclusive calculation of such characteristic figures. A system designed on that basis can be described as a monitoring system (Fig. 6). The following fundamental aspects are important: •

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Of primary importance to production management are statements concerning capacities, together with their lead times, utilization, schedule deviation and inventory. On the other hand, the clerical staff responsible for orders and consequently for sales, are more concerned with delivery time, therefore with order lead time, due delivery time observance and orders-in-hand. Finally, three accuracy stages are necessary (short, medium and long-term). Short-term accuracy is a matter of throughput of orders-in-hand to suit time limits by methods of adjustment of shortterm capacity (overtime, extra shifts), and priority control. In the medium-term it must be ensured that the delivery and work place lead times tally with those accepted in job scheduling. Therefore it is necessary to adjust capacities and inventories

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Production planningand control planned orders and "job shop" containing the released orders (work-in-process). The job shop itself consists of numerous work centers. The resulting manufacturing flows between the work centers continuously change according to the mix of orders. For example, Fig. 7 emphasizes the resulting flow of orders affecting a single machine (finishing lathe). Each work center acts as a funnel: the outlet represents the capacity, the filling exposes the current order queue and the channels show the flow or orders to and from the work center. Figure 7 also lays open the essential events in the flow of orders through the whole system: 1. 2. 3. 4. 5.

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(order definition) (start of manufacturing flow) (arrival at a work center) (departure from a work center) (end of manufacturing flow).

These events depend on various decisions made by the manufacturing controller involved who requires effective manufacturing control techniques paying regard to the fundamental aspects of a monitoring system mentioned above. 3.2. Shopfloor control For permanent process improvement a knowledge of the dynamic relations between the four mentioned logistic targets is essential. The throughput diagram also forms an effective basis for this. It is first of all necessary to explain the dependence of lead time on inventory and production output. Figure 8 illustrates the real throughput diagram of a workplace, on which straight input and output lines have been superimposed. If the gradient of the straight input line is the same as that of the straight output line, the relationship shown in the hatched triangle applies. One can

• H.-P. WIENDAHL

see from this that the mean weighted lead time is equal to mean inventory divided by mean production output. This relation, the so-called funnel formula, is the more accurate, • • •

the less the average volume of incoming work deviates from the volume of completed work, the less and the more uniform is the work content of the individual orders, and the fewer the sequence order changes in the waiting queue.

A control procedure already put into effect in accordance with these proposals is load-oriented order release, which controls the input to workplaces and consequently controls mean lead time through mean inventory. Figure 9 clarifies the basic concept, again in the form of a funnel model. The theoretical principles of the method are documented in comprehensible form in Ref. 6. The function of the method can be represented in characteristic operating curves (Fig. 10). The top curve represents production output when mean inventory in the work systems is changed by means of the "load barrier" control parameter. After a suitable inventory level, despite a further increase of inventory, production will no longer increase, because all work systems are busy. Only below this value is production decreased, at first gradually and then increasingly rapidly, because with increasing frequency more and more work systems no longer have work to do. At the same time there is a change in mean weighted lead time through the work systems. Above the appropriate inventory value, the relationship "mean weighted lead time = mean output/mean inventory" is followed fairly closely. Below that value the theoretical minimum is approached; this consists of the sum of mean implementation time and mean transport time. It is

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therefore in practice a matter of adjusting the appropriate inventory level so that sensible utilization is achieved on the one hand and unnecessarily high inventories avoided on the other. This at the same time produces the practical minimum lead time. This is achieved in practice by a gradual reduction of the load barrier.

4. EXPERIENCE WITH L O A D - O R I E N T E D MANUFACTURING CONTROL The system of load-oriented order release was offered to a wider public in Germany for the first time in 1981. Since then, a large number of electrical, electronic and mechanical engineering factories in the Federal Republic of Germany, the former German Democratic Republic, Austria, Switzerland and The Netherlands have successfully installed this system. Well-known business consultants and computer manufacturers offer ten different versions of the system either as an addition within the framework of PPC systems or as an autonomous unit of a personal computer system communicating with a main data processing system by data transfer. The system has since been supplemented by further modules not only including release but also scheduleoriented capacity planning and monitoring of the production process on the basis of characteristic figures and graphs explained earlier. Therefore, we call the whole system load-oriented manufacturing control.

Data from a mid-size pump-building company 7 are shown as an example of experience gained with loadoriented manufacturing control. The reasons this company introduced a load-oriented manufacturing control system were: •

• • • •

too long delivery times because of missing parts, which must be manufactured to complete a component intolerably long order lead times, on average 38 shop calendar days (SCD) low on-schedule delivery due to wrong scheduled lead times large stock-on-hand valued at half annual turnrover the installed PPC system could not remedy these problems.

In this company, the targets to be achieved through load-oriented manufacturing control were divided into two steps and had the following final values: decrease order lead time from 38 to 18 days, decrease schedule deviation from 35 to 0 days, increase output from 750 to 950 h/day, reduce inventory by 35%. In addition to these targets the transparency of job shop production should be increased by a clearly arranged presentation of all movement data through the monitoring system. Figure 11 shows an extended throughput diagram of the actual transactions of the total shop within 12 weeks from April to June 1989 based on real data from the pump-building company. The chart shows that at

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the beginning orders with a total load of 49,000 hours were present. About 26,000 hours were released. Almost 10,000 hours (between O U T and EXT) were already completed, whereas about 7000 hours (between INP and O U T ) were available in the queues on hand at the work centers and 8000 hours were still in transit. The cumulative curves show how, due to loadoriented manufacturing control, circular inventory (between REL and EXT) decreases during the following 12 weeks to 21,000 hours and despite the fluctuation of order entry (ENT) the other curves stay steady. Figure 12 shows average order lead times and delays for 12 weeks from July to September 1987. At this time only the monitoring system was installed. Actual (LT) and planned (LT-P) order lead times (from release to exit) were too long (37.5 and 37.8 days). They were set the same deliberately in order to start the planning system with realistic values. However, order release (DEL-REL) and delivery (DELEXT) were late by about 7 weeks (34.7 days and 34.3

days) as the due date planning was totally unrealistic. The whole situation improved in 1989 after installing the planning system. Figure 13 exposes the same key data as Fig. 12. Certainly actual lead times (28.3 SCD) were still longer than planned lead times but clearly shorter than in 1987. Delays for order release were already eliminated and for order exit reduced by 74~ since 1987. The benefits of the new system can be summarized as follows. Lead times and inventory were reduced by one-fourth and delivery delays were cut from 7 weeks to 1.5 weeks. Delivery increased by 17~. It is realistic to expect that the company will reach its future targets with the help of load-oriented manufacturing control. The results up to now show that the new system enables the factory: • to reduce lead times and inventories • to keep actual lead times at the planned level • to meet the planned due dates • to guarantee a high work center utilization.

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Experiments under investigation show that simulation increasingly will gain ground, both in the framework of general control and also in that of mediumterm and fine control. Whilst investigations of order control and capacity control are advocated under the scope of general control, job-scheduling control and order control, simulation offers possibilities for investigating ideal capacity flow, probable order throughput and determination of optimum batch throughput size; again, under the scope of fine control, optimum processing sequences can be investigated. In the foreseeable future, therefore, the production process for piece-goods will bear an increasingly strong resemblance to a flow type processing system which is

illustrated, monitored and controlled with the help of process models, s REFERENCES 1. Wiendahl, H.-P.: The throughput diagram a universal model for the illustration, control and supervision of logistic processes. Ann. CIRP 37(1): 465-468, 1988. 2. Kettner, H., Bechte, W.: New methods of production control by load-orientated order release. VDI-Z 123: 459-466, 1981. 3. Wiendahl, H.-P., Dombrowski, U.: Manufacturing routine analysis for the quantitative comparison of conventional and flexible manufacturing. Int. J. Advanced Manufacturing Technol. 2(4): 41-62, 1987. 4. Bechte, W.: A control and planning system for loadorientated production control in conversational mode.

Production planning and control • H.-P. WIENDAHL Concept and realization. In: The Practice of Load-Orientated Production Control Wiendahl, H.-P. (ed.). Munich, 1986, pp. 89-118. 5. Bechte, W.: Load-orientated manufacturing control, case study: how to make the funnel-model work. APICS 31st Annual International Conference, Las Vegas, Nevada, 17-21 Oct. 1988. 6. Wiendahl, H.-P.: Load-Orientated Production Control Munich, Hanser, 1987.

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7. Holzhiiter, E., Friedrichs, W.: Experiences with KPSF, a system for load-oriented manufacturing control in a midsize mechanical engineering company. In: Load-Oriented Manufacturing Control Wiendahl, H.-P. (ed.). Munich, 1989, pp. 279 299. 8. Wiendahl, H.-P.: Fundaments and experiences with loadoriented manufacturing control. APICS Conference, New Orleans, 1990.