Production Release Control and the Push/Pull and Make-to-Order/Make-to-Stock Distinctions

Transcription

1 STOCHASTIC MODELS OF MANUFACTURING AND SERVICE OPERATIONS SMMSO 2013 Production Release Control and the Push/Pull and Make-to-Order/Make-to-Stock Distinctions George Liberopoulos Department of Mechanical Engineering, University of Thessaly, Volos, Greece, We consider three elementary mechanisms for controlling the release of parts for production in manufacturing systems: 1) controlling raw part arrivals, 2) authorizing releases based on work-in-process, and 3) responding to actual demands. We discuss different variants of these mechanisms on a simple production system, and we use these variants as a basis to revisit the push/pull and make-to-order/make-to-stock distinctions. Key words : production release control; push; pull; make-to-stock; make-to-order; 1. Introduction The last two decades have seen a surge in the literature related to pull control, WIP control, and token-based production control systems. Despite this intensive activity in the literature, the definition of certain important concepts remains unclear. An important concept that is still a source of confusion is the push/pull distinction and its relationship to the make-to-order (MTO)/maketo-stock (MTS) distinction. The characterizations of the push/pull distinction that have appeared in the literature can be summarized into the following three definitions: Definition 1. A pull system initiates production as a reaction to current demand, while a push system initiates production in anticipation of future demand (e.g., Karmarkar (1989), Nahmias (2009)). Definition 2. In a pull system production is triggered by actual demands for finished products, while in a push system production is initiated independently of demands (e.g., Vollmann et al. (2005), Zipkin (2000), Liberopoulos and Dallery (2000)). Definition 3. A pull system is one that explicitly limits the amount of WIP that can be in the system, while a push system has no explicit limit on the amount of WIP that can be in the system (e.g., Hopp and Spearman (2004), Karrer (2012), Gonzlez-R et al. (2012)). Although the push/pull distinction is still an open issue, the MTO/MTS distinction should be easier to agree on. The MTO/MTS distinction has to do with whether finished goods are produced to be stocked or to fill specific customer orders (demands). Somewhere in between MTO and MTS, but perhaps closer to the latter, lies the notion of make-to-forecast (MTF). In this paper, we adopt the following definition: Definition 4. In a MTO system, production releases are initiated to meet actual customer orders (demand), while in a MTF system, production releases are initiated to meet forecasts of customer orders. In a MTS, production releases are initiated to replenish the finished goods inventory and bring it up to a specified target level. Therefore, in MTO systems, production follows demand, while in MTF and MTS systems, production precedes demand, where the demand is timed at the due date and not the arrival time of a customer order. Our goal in this paper is to try to sort out the above concepts. To this end, we look at different production control systems with controlled raw part arrivals, with/without WIP control, where the demands for finished goods do/do not generate further demands upstream of the finished goods buffer. We use the latter distinction to characterize the systems as push or pull, based on Definition 2. We argue that the MTO/MTS distinction, which has to do with the timing of production releases 113

2 114 SMMSO 2013 Figure 1 Production system with no WIP control and demands for finished goods only relatively to the timing of demands, only makes sense in pull systems, because in push systems, production is initiated independently of demands. Moreover, we argue that MTF systems can be either pull or push, depending on whether forecasts are based on actual demands or are generated independently of the demands. 2. System with no WIP control and demands for finished goods only Figure 1 shows a basic production system consisting of four workstations in series, denoted by WS i, i =1,, 4, separated by buffers of infinite capacity, denoted by P i, i =1,, 3. Each workstation consists of a machine, represented by a circle, with an input buffer of infinite capacity before it. Downstream of WS 4 there is a finished goods buffer, denoted by P 4.UpstreamofWS 1 there is a raw parts buffer, denoted by P 0, which receives raw parts that arrive according to a controlled raw part arrival process, denoted by RP. RP can be thought of as the machine of a pseudo-workstation that is supplied by an infinite source of parts. The production rate of RP (i.e., the raw part arrival rate) sets the production pace for the rest of the system. We assume that when the machine of workstation WS i works on a part, it processes it at full speed. When it finishes the part, it pushes it to the input buffer of the next downstream workstation, WS i+1 (or to the finished goods buffer P 4,ifi = 4), and starts working on a new part which it pulls from its input buffer. If no part is available there, the machine is starved. The part that is pushed downstream passes through buffer P i but does spend any time in P i, except in the case of buffer P 4 ; hence P i, i =1,, 3, is always empty. The same holds for buffer P 0 which is fed by RP. As buffers P 0 to P 3 are always empty, they are drawn with dotted lines. The finished goods coming out of WS 4 are stored in P 4 waiting to be matched to customer demands for finished goods that arrive to buffer D 5. Normally, the production rate of RP should be set equal to the average demand rate, so that eventually all the finished parts will be matched to demands and vice versa. In this case, the number of parts in buffer P 4 and the number of demands in D 5 will be finite. Note that the incoming customer demands are for finished goods only and do not generate any further demands for semi-finished goods or raw parts. Therefore, the entire system upstream of P 4 is not informed of the demands and produces parts with no control other than that stemming from the controlled raw part arrival process RP. This type of control is completely exogenous, because it does not take into account either the state of the system or the external disturbance that is supposed to drive the system (demand). Based on both Definitions 2 and 3, the system is push; in the case of Definition 2, because production is initiated independently of demands, and in the case of Definition 3, because the WIP in the system is not limited. Definition 1 does not cover this system. Moreover, based on Definition 4, the system is neither MTO nor MTS, since it produces parts neither to meet actual customer orders (demands) nor to replenish finished goods inventory when it is depleted by demands. 3. System with no WIP control and demands for finished goods generating demands for raw parts Figure 2 shows a system which is identical to the system in Figure 1, except that each incoming customer demand for finished goods also generates a demand for a raw part that is transfered to

3 SMMSO Figure 2 System with no WIP control and demands for finished goods generating demands for raw parts (basestock system) buffer D 1.Now,inorderforarawparttoenterWS 1, not only must such a part exist in P 0, but a demand for it must also exist in buffer D 1. Although the release of raw parts into the system is still controlled by the exogenous raw part arrival process RP, it is also driven by demands. If the production rate of RP is set higher than the production rate of WS 1, then the raw parts buffer P 0 will eventually be flooded with infinite raw parts. In this case, the system will have given up the raw part arrival control, but the demand response element will still be there. Normally, the processing rate of RP should be set equal to the demand rate, in which case buffer P 0 will not grow to infinity. In this case, process RP plays an important control role as it sets a limit on the release pace. Thus, if a very large number of customer demands arrive in a short period of time, RP prohibits the release of an equal number of raw parts into WS 1, which may unnecessarily burden the WIP. Contrary to the system in Figure 1, the initial state of buffer P 4 in the system in Figure 2, denoted by S 4, matters, because it sets an upper limit for this buffer. This limit will be reached again and again if no customer demands arrive to the system for a long enough time so that the rest of the system will have been cleared out of parts. Many readers will recognize the system in Figure 2 as a base-stock system, wheres 4 is the base-stock level. Based on Definitions 1 and 2, the base-stock system is pull, because the release of parts for production at the entrance of the system is driven by actual demands. Another way to look at this is that the base-stock system is pull because the production release decision at the entrance of the system is based on system status, where by system status Definitions 1 and 2 imply the inventory position (pending orders in D 1 + WIP in all work stations + on-hand inventory of finished parts in P 4 backordered demands in D 5 ) of finished goods. More specifically, the rule that drives production release decisions in the base-stock system is that the inventory position must always be constant and equal to S 4. If, however, by system status we mean WIP only, then the base-stock system is certainly not pull. In fact, based on Definition 3, which equates system status with WIP, the base-stock system is push. Finally, based on Definition 4, the base-stock system is MTO, if S 4 = 0, and MTS, if S 4 > System with WIP control and demands for finished goods generating demands for raw parts In this section, we look at two systems with WIP control in which the demands for finished goods also generate demands for raw parts. The difference between the two systems is that in the first system, the demands for semi-finished goods and raw parts are carried upstream by production authorization (PA) cards, which are used to implement WIP control, while in the second, they are transferred upstream independently of the PA card movement System where demands are carried upstream by PA cards (CONWIP) The system in Figure 3 looks like the system in Figure 1 on which a CONWIP (or single-stage kanban) mechanism has been superimposed to control the WIP. However, there is a fundamental

4 116 SMMSO 2013 Figure 3 Production system with CONWIP control and demands for finished goods generating demands for raw parts difference between the two systems, regarding the demands. Namely, in the system in Figure 1, each incoming customer demand for finished goods does not generate any further demands upstream of buffer P 4. In the CONWIP system in Figure 3, on the other hand, each incoming customer demand for a finished part in PA 4 also generates a demand for a raw part stored in P 0, as was the case in base-stock system in Figure 2. Unlike in the base-stock system, however, this demand is not transferred to DA 1 instantly upon the arrival of the customer demand that generated it; instead, it is carried upstream by a returning free PA card (kanban). More specifically, each time a PA card is freed from buffer PA 4 and is returned upstream to buffer DA 1, it carries with it a demand for a raw part in P 0. The buffer of free PA cards is denoted by DA 1 instead of by A 1 to indicate that it contains authorization cards ( A ) attached to demands ( D ). In summary, the returning PA cards in the CONWIP system have two functions: firstly, they limit the WIP, and secondly, they carry the demands upstream. Based on all Definitions 1 3, this system would be characterized as pull; in the case of Definitions 1 and 2, because of the second function, whereas in the case of Definition 3, because of the first function. The initial state of buffer PA 4 is equal to the WIP cap K 1 4. Hence, K 1 4 plays the role of the target inventory level of finished goods, which is played by S 4 in the base-stock system. Unlike S 4, K 1 4 must be necessarily positive, because if it were zero, no raw part would ever be authorized to be released into the system. This implies that the CONWIP system in Figure 2 is necessarily MTS and cannot possibly be turned into MTO by setting K 1 4 equal to zero. Does this also mean that WIP control necessarily implies a MTS system and that WIP control and MTO cannot coexist? The answer is that they can coexist if the function of transferring the demands upstream is uncoupled from the function of limiting the WIP via the PA card return movement. This is shown next System where demands are carried upstream independently of PA Cards (extended CONWIP) Figure 4 shows a system in which the demand flow is uncoupled from the PA card flow. It is identical to the base-stock system in Figure 2 on which a CONWIP (single-stage kanban) mechanism has been superimposed to control the WIP. We refer to it as an extended CONWIP system, because it is equivalent to an extended kanban control system with only one stage (see Liberopoulos and Dallery (2000)). In the extended CONWIP system, each incoming customer demand for finished goods also generates a demand for a raw part stored in P 0, as was the case with the simple CONWIP system in Figure 3. Unlike that system, however, this demand is transferred upstream to buffer D 1 immediately upon the arrival of the customer demand to the system, as is the case in the base-stock system, instead of waiting to be taken upstream by a returning PA card. The number of PA cards in the extended CONWIP system is still K 1 4,aswasthecaseinthe simple CONWIP system, only now the initial state of buffer PA 4 is not equal to K 1 4 ; instead,

5 SMMSO Figure 4 Production system with extended CONWIP control and demands for finished goods generating demands for raw parts Figure 5 Production system with (K, S) control and demands for finished goods generating demands for raw parts it is equal to the base-stock level, S 4,whereS 4 K 1 4, as was the case in the base-stock system. The S 4 parts that are initially stored in buffer PA 4 have an equal number of PA cards attached to them. The rest of the PA cards, namely, K 1 4 S 4, are initially stored in buffer A 1. Dallery and Liberopoulos (2000) show that when K 1 4 = S 4, the extended CONWIP system in Figure 4 is identical to the CONWIP system in Figure 3. The extended CONWIP system would be characterized as pull, based on all Definitions 1 3; in the case of Definitions 1 and 2, because production release decisions are driven by customer demands, whereas in the case of Definition 3, because the WIP in them is limited. Moreover, as as was the case with the base-stock system, the extended CONWIP system is MTS, if S 4 > 0, and MTO, if S 4 =0. The system in Figure 5 shows a modification of the the extended CONWIP system, in which the PA cards are released and returned to buffer A 1 when finished parts exit WS 4, instead of when they exit the finished goods buffer. Liberopoulos and Dallery (2002) call the system in Figure 5 a (K,S) system. They argue that when K 1 4 =, the(k,s) system is equivalent to the basestock system. When K 1 4 S 4,the(K,S) system is equivalent to the extended CONWIP system, and when K 1 4 <S 4, it is equivalent to what Buzacott and Shanthikumar (1993) call a local control policy system. 5. System with WIP control and demands for finished goods only The systems with WIP control we have seen thus far are pull systems, because according to Definition 2, which we adopt here they release parts into the system in response to demand. More specifically, in all these systems, the demands for finished goods also generate demands for raw parts that are eventually transferred upstream the system and drive production releases. This

6 118 SMMSO 2013 Figure 6 Production system with CONWIP control and demands for finished goods only raises the question of whether all systems with WIP control is necessarily pull systems, as Definition 3 implies. Figure 6 shows a system that combines the system in Figure 1, as far as demand transfers are concerned, and the WIP control mechanism of the (K,S) control system in Figure 5. Note that the incoming customer demands are for finished goods only and do not generate any further demands for raw parts. Consequently, the entire system upstream of P 4 is not informed of the demands; therefore, the production release depends only on the exogenous (open-loop) process RP and the state-dependent (closed-loop) WIP control imposed by the PA card loop. This type of control does not take into account the external disturbance that is supposed to drive the system, namely, the demand. For this reason, we would characterize the system as push, based on Definition 2. We note, however, that according to Definition 3, the system is pull, because of the state-dependent WIP control. Definition 1 does not cover this system. As we adopt Definition 2, we consider the system as being neither MTO nor MTS, because parts are neither produced to meet specific orders (demands) nor to replenish finished goods inventory when it is depleted by demands. Moreover, the initial state of the buffers does not matter. As was the case with the system in Figure 1, if the production rate of RP is set equal to the average demand rate, then eventually all the finished parts will be matched to demands and vice versa. In this case, the system in Figure 6 will behave like a takt-paced production system with WIP control, in which the demand rate establishes the pace or takt time rather than chasing (responding to) demand (see Hopp and Spearman (2004)). 6. Production control systems with forecasts The systems that we have looked at thus far are driven by actual demands, namely, customer requests for the immediate delivery of finished goods. Often in practice, production is planned based on forecasts of future demands. One of the traditional methods for generating forecasts is to use past demand information (time series method). Figure 7 shows a system which is similar to the (K,S) system in Figure 5, except that the demand for a raw part that is generated by each arriving customer demand is not immediately transferred to buffer D 1, but is fed into a forecast generator, denoted by FG, that generates forecasts of future customer demands T time units into the future, based on past demand information. In this case, T stands for the forecast horizon. Regardless of the exact forecasting method used, the FG black box should act so as to smooth out the incoming demand stream into a less variable outgoing stream of forecasts. Naturally, on average, the demand forecasts should match the actual demands. Once a demand forecast for T time units into the future is generated, a demand for a raw-part in buffer P 0 is released into buffer D 1 with a delay which is determined by offsetting the forecasted demand due-date by the planned production lead-time L, as is done in the time-phasing step of the MRP procedure.

7 SMMSO Figure 7 Production system with (K, S) control and demands for finished goods generating forecasts for raw parts The point to make here is that, as the release of raw parts into the system is driven by the forecasts, which are generated by the demands, the system is still a pull system, according to Definition 2. Based on Definition 1, on the other hand, the same system might be characterized as push, because production is initiated in anticipation of future demands. Finally, based on Definition 3, it would be characterized as pull, but only because of the WIP control. Concerning the MTO/MTS distinction, things are a bit less obvious. Clearly, the inventory position of the system in Figure 7 is not always constant and equal to S 4,aswasthecasewiththe (K,S) system in Figure 5, because in any given time interval, the number of forecasted demands that exit FG is not necessarily equal to the number of actual demands that have entered FG. Still, however, the inventory position will be constant and equal to S 4 on average, because as we mentioned earlier, on average, the forecasted demands exiting FG should match the actual demands entering FG. With this in mind, if S 4 > 0 the system in Figure 7 is still a MTS system, because S 4 is still a target for the finished goods inventory. If S 4 = 0, on the other hand, we would characterize the system as MTF rather than MTO; however, as the forecasts are generated by the demands (orders) we denote this type of MTF as MTF/O. Finally, we should mention that there are other methods for generating forecasts which do not use past demand information. Figure 8 shows a system which is similar to the system in Figure 7, except that the forecasts for finished parts and hence the forecasted demand for raw parts are generated independently of the demands. In this case, based on Definition 2, we would characterize the system as a push system in which raw-parts are released in a MTF mode. As the forecasts are external and do not depend on the demands, we denote this type of MTF as MTF/E. Based on the discussion above concerning the two systems with forecasts, we conclude that a system which is driven by forecasts can be either pull or push, depending on whether the forecasts are generated based on the demands or not. Based on Definition 1, both systems would be characterized as push. 7. Conclusions In this paper, we adopted Definition 2 regading the push/pull distinction, because we find that this definition is clearer than the others. We also argued that the MTO/MTS distinction only makes sense for pull systems, because push systems disregard demand. Definition 1 seems to leave out the case where production is initiated independently of demand, as in the takt-paced systems in Figures 1 and 6. Definition 3 does not distinguish between the case where a signal authorizing the release of a new part for production in a manufacturing system is generated when a part finishes its processing in the system, as in Figure 6, and the case where such a signal is generated when a

8 120 SMMSO 2013 Figure 8 Production system with CONWIP control, demands for finished goods, and independent forecasts for raw parts finished part (a part which has finished its processing in the system) is consumed by a demand, as in Figure 3. Although we adopted Definition 2, we agree with Hopp and Spearman (2004), who propose Definition 3, that the key benefits of a pull system arise when it establishes a WIP limit. Indeed, the (K,S) system in Figure 5, which is a pull system with a WIP cap, includes the base-stock system as a special case, and so it clearly performs better than it. It also includes the CONWIP system in Figure 3 as a special case, and so it performs better than that system too. This observation alone points to the potential benefits of uncoupling the transfer of demands from the kanban return movement used to limit the WIP. Acknowledgments The work in this paper was supported by grant MIS Odysseus: A holistic approach for managing variability in contemporary global supply chain networks, which was co-financed by the EU ESF and Greek national funds through program: THALES: Reinforcement of the interdisciplinary and/or inter-institutional research and innovation of the Operational Program Education and Lifelong Learning of the NSRF. References Buzacott, J.A., J.G. Shanthikumar Stochastic Models of Manufacturing Systems. Prentice-Hall, Englewood Cliffs, NJ. Dallery, Y., G. Liberopoulos Extended kanban control system: Combining kanban and base stock. IIE Transactions 32(4) Gonzlez-R, P.L., J.M. Framinan, H. Pierreval Token-based pull production control systems: An introductory overview. Journal of Intelligent Manufacturing Systems 23(1) Hopp, W.J., M.L. Spearman To pull or not to pull: What is the question? Manufacturing and Service Operations Management 6(2) Karmarkar, U Getting control of just-in-time. Harvard Business Review 66 (Sep-Oct) Karrer, C Engineering Production Control Strategies: A Guide to Tailor Strategies that Unite the Merits of Push and Pull. Series in Management for Professionals, Springer, Heidelberg. Liberopoulos, G., Y. Dallery A unified framework for pull control mechanisms in multi stage manufacturing systems. Annals of Operations Research 93(1-4) Liberopoulos, G., Y. Dallery Base stock versus wip cap in single-stage make-to-stock productioninventory systems. IIE Transactions 34(7) Nahmias, S Production and Operations Analysis 6/E. McGraw-Hill, Boston. Vollmann, T.E., W.L. Berry, D.C. Whybark, F.R. Jackobs Manufacturing Planning and Control for Supply Chain Management 5/E. McGraw-Hill, Boston. Zipkin, P.H Foundations of Inventory Management. McGraw-Hill, Boston.