A distinction is frequently made between push and pull production planning and control systems. Many people believe that pull systems are inherently better at reducing stocks because they try to eliminate queues, not provide for them, whereas push systems encourage queues to cushion operations and to increase work station utilisation but at higher cost. However, the definitions of push and pull are inconsistent between different researchers. Worse, arguments about performance are sometimes circular. Thus, if the performance of a pull system is poor then it may be suggested that this is because the fundamentals of JIT are not being observed, whereas, if the performance of a push system is poor, then that is a consequence of it being a push system. After defining push and pull systems, this paper examines, by means of simulation, the effect that push and pull information flows have on system performance, under a variety of conditions. In particular, the performance of both push and pull information flow systems are considered in conjunction with high-quality levels, small set-ups and small batches, i.e. the conditions normally associated with JIT continuous improvement programmes. Similarly, the performance of both push and pull information flow systems are investigated in the presence of conditions such as large set-up times, which are frequently eliminated as part of a continuous improvement programme. The question investigated in this study is how system performance is affected by the flow of control information. The investigation uses models of the material and information flows of push and pull systems to examine the conditions which affect performance. A production sequence is chosen which consists of ordering materials, making parts and assembling products which are then despatched to customers. A set of decision rules is used to operate the systems using different demand and inventory level data.
1. Introduction
Many push and pull material control systems have been implemented. MRP is frequently described as a push system. A kanban operated JIT system is usually considered to be a typical pull system. However, closer examination shows that most practical systems consist of both push and pull. For example, a system which operates mainly by local pull control may use a push system to obtain long lead time items. The Toyota system, the classical pull system, uses push information flow for the vehicle and pull information flow based on kanbans to ensure the availability of other parts on the assembly track. Similarly, a MRP system may use local progress chasing to pull items through the manufacturing process.
Our study investigated whether there was any difference in performance as a direct result of using push-or-pull information flows. A brief summary of some published material on push and pull systems and their performance is presented. From this it is clear that some inequitable comparisons have been made. This immediately raises the question of how push and pull should be defined. This paper proposes definitions related to information flows and then models several examples of each system. The performance of each system is then derived and compared.
2. Some definitions of push and pull systems
It has already been observed that most manufacturing control systems are hybrid, i.e. a mixture of both push and pull. However, this observation is not very meaningful if the terms push and pull have been left deliberately vague. In order to clarify the terms, we examined papers which discussed the performance of push and pull systems. The papers are broadly of two kinds: firstly those by authors who have tried to investigate push and pull systems by simulation and, secondly those by authors who have looked more descriptively at manufacturing systems. Broadly, the former investigate well-defined manufacturing sub-systems whilst the latter have a wider perspective, perhaps referring to the whole enterprise. The simulation modelling examples refer to push and pull to identify the type of system, but necessarily then go on to define in detail the rules of operation and other parameters which describe the system modelled. This makes it very difficult to compare directly the results of these studies. Views of some of the authors are now described:
Lee [1]described procedures for push and pull as follows:
Push
Jobs on entry into the system are queued at the first required process. Queue priority is resolved according to the selected scheduling rule. On completion of a process, the job proceeds to subsequent processes on the designated process route. When all processes are completed the job exits from the system [1].
Pull
Activities at the process station are triggered by depleted output kanban stock at the process stations. Each depleted kanban stock constitutes a queue unit at the station. Before a job can be loaded a check is made to ensure that the precedence constraint is satisfied; that is, there must be sufficient inventory in the output kanban stock of the upstream processes of that job. If so, a draw is made from the output kanban stock. Should this cause the output kanban stock to fall below the re-order level, the job is queued at that station [1].