Mark L. Spearman

CONWIP : A Pull Alternative to Kanban

SUMMARY This paper describes a new pull-based production system called CONWIP. Practical advantages of CONWIP over push and other pull systems are given. Theoretical arguments in favour of the system are outlined and simulation studies are included to give insight into the systems performance.

Push and pull production systems: issues and comparisons

Concerns about American manufacturing competitiveness compel new interest in alternative production control strategies. In this paper, we examine the behavior of push and pull production systems in an attempt to explain the apparent superior performance of pull systems. We consider three conjectures: that pull systems have less congestion; that pull systems are inherently easier to control; and that the benefits of a pull environment owe more to the fact that WIP is bounded than to the practice of “pulling” everywhere. We examine these conjectures for analytically tractable models. In doing so, we not only find supporting evidence for our surmises but also identify a control strategy that has push and pull characteristics and appears to outperform both pure push and pure pull systems. This hybrid system also appears to be more general in its applicability than traditional pull systems such as Kanban.

Throughput of a constant work in process manufacturing line subject to failures

We consider a production line consisting of several machines in tandem operating under a constant work in process (CONWIP) control strategy. We assume that processing times are deterministic but machines are subject to exponential failures and repairs. We model this system as a closed queueing network and develop an approximate regenerative model (ARM) for estimating throughput and average cycle time as a function of WIP level. We compare ARM with mean value analysis (MVA) and develop readily computable tests of the suitability of the two approaches to a given production system. Through comparison with simulations, we show that ARM gives better predictions than MVA in a range of realistic situations.

Customer service in pull production systems

In this paper, we consider the issue of customer service in pull production systems. We first discuss the meaning of customer service in a pull system and contrast it to push systems. We also discuss both pure and hybrid pull systems that are found in the literature. We then investigate the effects of changing inventory levels and processing time characteristics on customer service in a pure kanban system. Finally, we show that a hybrid system known as CONWIP not only has better service than a pure kanban system, but also solves certain implementation problems.

Easily Implementable Inventory Control Policies

This work was initiated and supported by a manufacturer of mail processing equipment, which stocks 30,000 distinct parts in a distribution center to support field maintenance of their equipment. To find an effective stocking policy for this system we formulate a constrained optimization model with the objective of minimizing overall inventory investment at the distribution center subject to constraints on customer service and order frequency. Because size, integrality, and nonconvexity make this problem intractable to exact analysis, we develop three heuristic algorithms based on simplified representations of the inventory and service expressions. These lead to what we call easily implementable inventory policies, in which the control parameters for a newly introduced part can be computed in closed form without reoptimizing the rest of the system. Numerical comparisons against a lower bound on the cost function show that even our simplest heuristic works well when a high service level is required. However...

Using an optimized queueing network model to support wafer fab design

We develop an Optimized Queueing Network (OQNet) capacity planning tool for supporting the design of new and reconfigured semiconductor fabrication facilities that makes use of queueing network approximations and an optimization routine. The basic problem addressed by this tool is to minimize the facility cost required to meet specified volume and cycle time targets. Features common to semiconductor environments, such as batch processes, re-entrant flows, multiple product classes, and machine setups, are incorporated into the model. Comparisons with simulation show that the queueing and other approximations are reasonably accurate. Tests of the optimization routine demonstrate that it can find good solutions quickly.

An easily implementable hierarchical heuristic for a two-echelon spare parts distribution system

This paper addresses a two-echelon spare parts stocking and distribution system consisting of a central Distribution Center (DC) and regional facilities. Because the primary purpose for holding inventory is to provide timely repairs of customer′s equipment, we set as our objective to minimize total inventory investment subject to constraints on the delay due to parts outages. We decompose the resulting problem by level and by facility. By simplifying the expressions for the delay constraints and applying previously developed heuristics for the single-level problem [1], we are able to derive closed-form expressions for the inventory control parameters. We then develop a search algorithm (on DC fill rate) to approximate the parameters (Lagrange multipliers) in the closed-form expressions. Numerical comparisons against an analytic lower bound and, for small problems, exact solutions show the approximation to be quite accurate. We also found that it outperforms methods currently in use by the firm that motivated this work. Finally, because it yields closed-form expressions for inventory control parameters and the parameters are only updated periodically, the policy is “easily implementable” once suitable Lagrange multipliers have been computed.

SETTING SAFETY LEADTIMES FOR PURCHASED COMPONENTS IN ASSEMBLY SYSTEMS

We consider the problem of setting appropriate safety leadtimes in an assembly system where all components are purchased and the only manufacturing operation is final assembly. First, we describe two formulations of this problem: (1) minimize total inventory carrying and tardiness costs and (2) minimize inventory carrying costs subject to a service constraint. Second, we discuss how these formulations sometimes fail to adequately provide a decision maker with sufficient information to establish leadtimes when applied independently but how they can be used together to provide a useful decision support system. Finally, we describe a procedure similar to ABC analysis that allows us to solve a much smaller related problem whose solution provides a good approximation to the solution of the original problem. We conclude the paper with numerical examples and a discussion of an actual implementation.

ECONOMIC PRODUCTION QUOTAS FOR PULL MANUFACTURING SYSTEMS

We consider the problem of using “safety capacity” to ensure due date integrity in a pull manufacturing system and quantify the basic tradeoff between lost revenue opportunity and overtime costs. In this context, we address the question of when it is economically attractive to use “under capacity scheduling” and the problem of setting economic production quotas. We develop four models for addressing the quota setting problem. The first three assume that quota shortfalls cannot be carried over to the next regular time production period. Models 1 and 3 assume that these shortages are made up on overtime and incur fixed or fixed plus variable costs. Model 2 does not use a capacity buffer and treats shortages as lost sales. Finally, Model 4 assumes that shortages can be backlogged to the next regular time production period at a cost. For this model, we compute both an optimal quota and an overtime “trigger,” which represents the minimum shortage for which overtime is used. We give computational results that i...

Improving the design of stochastic production lines : an approach using perturbation analysis

Abstract With the recent increase in expense and specialization of equipment, capacity decisions have taken on greater significance. As a result, companies are in need of a better understanding of the investment tradeoffs. In this paper, we examine the problem of determining the most profitable capacity configuration for a production line modelled as a series of single-server stations. In the context of a constant work-in-process (CONWIP) control system, an algorithm is developed for solving the general problem using a single-run simulation procedure. Various market structures are examined and sensitivity analysis is performed on the cost of capacity, quality and the amount of work-in-process allowed in the system.