The effects of manufacturing control strategies on the cash conversion cycle in manufacturing systems

Abstract It is a common practice to measure the performance of a manufacturing system using common production management criteria such as cell performance metrics or general operations management metrics among engineering management/business administration practitioners. However, most of the time, these performance measures do not truly reflect company's financial performance. It is not unusual to see a well performing operational strategy in terms of one or more cell performance metrics fail to produce the same level of financial performance. The aim of this study is to investigate the effects of the two most common manufacturing planning and control strategies, namely push and pull, on the cash conversion cycle (CCC) in a manufacturing system. The CCC is an important measure of the length of time between cash payment for the purchase of resalable goods or an investment made for production and the collection of accounts receivable generated by the sale of those purchased/produced goods. We have simulated a hypothetical multi-stage manufacturing system that is run under either push or pull control systems to measure the effects of these systems on the financial performance of the company. We used deterministic master production scheduling for the simulated production period to eliminate the variation generated by randomness so that a one-to-one comparison between manufacturing control strategies is made possible. We analyse the results generated by the two control strategies to understand their effects on the CCC and draw conclusions.

[1]  R. Cooper How Cost Accounting Distorts Product Costs , 1988 .

[2]  Timothy D. Fry,et al.  THE USE OF MANAGEMENT ACCOUNTING SYSTEMS IN MANUFACTURING , 1998 .

[3]  Andrew Kusiak,et al.  Manufacturing control with a push-pull approach , 1998 .

[4]  Mustafa Özbayrak,et al.  Activity-based cost estimation in a push/pull advanced manufacturing system , 2004 .

[5]  Trevor A Spedding,et al.  Application of discrete event simulation to the activity based costing of manufacturing systems , 1999 .

[6]  E. W. Walker Toward A Theory Of Working Capital , 1964 .

[7]  Robert A. Leitch Effect of stochasticity, capacity and lead time cost drivers on WIP and throughput in a pull production environment , 2001 .

[8]  Randall P. Sadowski,et al.  Introduction to Simulation Using Siman , 1990 .

[9]  Ömer Faruk Baykoç,et al.  Simulation modelling and analysis of a JIT production system , 1998 .

[10]  David T. Boyd,et al.  The effects of just-in-time systems on financial accounting metrics , 2002, Ind. Manag. Data Syst..

[11]  Tamás Koltai,et al.  A flexible costing system for flexible manufacturing systems using activity based costing , 2000 .

[12]  W. G. Sullivan,et al.  Impact of ABC information on product mix and costing decisions , 1995 .

[13]  Paul D. Hutchison,et al.  Cash‐to‐cash: the new supply chain management metric , 2002 .

[14]  Lloyd J. Taylor,et al.  A simulation study of WIP inventory drive systems and their effect on financial measurements , 1999 .

[15]  A. Thesen Some simple, but efficient, push and pull heuristics for production sequencing for certain flexible manufacturing systems , 1999 .

[16]  Soemon Takakuwa The use of simulation in activity-based costing for flexible manufacturing systems , 1997, WSC '97.