Are push and pull systems really so different

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.