Abstract
The basic principles of rapid modelling based on queueing theory, that provide the theoretical foundations for lead time reduction, are well known in research. We are globally observing an underinvestment in lead time reduction at top management levels. In particular, the maximization of resource utilization is still a wide-spread aim for managers in many companies around the world. This is due to inappropriate performance measurement systems as well as compensation systems for managers which neglect the monetary effects of lead time reduction. Therefore, we developed a model based on open queueing networks to evaluate the financial impacts of lead time reduction. Illustrated by an empirical case from the polymer industry, we will demonstrate the impact of performance measures on financial measures. That is why we will take into consideration efficiency performance measures (work in process, lead time, etc.) as well as effectiveness performance measure (e.g., customer satisfaction, retention rate). Based on our evaluation model, we will be able to investigate different scenarios to reduce lead time for the given case and evaluate these, based on the developed overall performance measurement model, i.e., optimization of the batch size, resource pooling, de/increase in the number of resources. In particular, we achieved a 75% lead time reduction and a 11% overall cost reduction (resource costs, setup costs, WIP costs, penalty costs, inventory costs) without changing the whole production layout or making high investments.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Askenazy, P., Thesmar, D., Thoenig, M.: On the relation between organisational practices and new technologies: the role of (time-based) competition. Economic Journal 116(508), 128–154 (2006)
Beamon, B.: Measuring supply chain performance. International journal of operations and production management 19(3), 275–292 (1999)
Bodie, Z., Kane, A., Marcus, A.: Essentials of investments, 5th edn. McGraw-Hill Irwin, New York (2003)
Bolch, G., Greiner, S., Meer, H., Trivedi, K.: Queueing networks and Markov chains: modeling and performance evaluation with computer science applications. John Wiley and Sons, New Jersey (2006)
Christopher, M., Towill, D.: Supply chain migration from lean and functional to agile and customised. Supply Chain Management: An International Journal 5(4), 206–213 (2000)
Croom S (2009) Introduction to research methodology in operations. In: Karlsson C (ed) Researching operations management, 1st edn, Routledge, New York
Ghalayini, A., Noble, J.: The changing basis of performance measurement. International Journal of Operations and Production Management 16(8), 63–80 (1996)
Govil, M., Fu, M.: Queueing theory in manufacturing: a survey. Journal of Manufacturing Systems 18(3), 214–240 (1999)
Grünberg, T.: Towards a method for finding and prioritising potential performance improvement areas in manufacturing operations. International Journal of Productivity and Performance Management 53(1), 52–71 (2004)
Hammel, T., Phelps, T., Kuettner, D.: The re-engineering of Hewlett-Packard’s CD-RW supply chain. Supply Chain Management: An International Journal 7(3), 113–118 (2002)
Haque, L., Armstrong, M.: A survey of the machine interference problem. European Journal of Operational Research 179(2), 469–482 (2006)
Hill, A., Collier, D., Froehle, C., Goodale, J., Metters, R., Verma, R.: Research opportunities in service process design. Journal of Operations Management 20(2), 189–202 (2002)
Hofmann, P., Reiner, G.: Drivers for improving supply chain performance: an empirical study. International Journal of Integrated Supply Management 2(3), 214–230 (2006)
Hopp, W., Spearman, M.: Factory physics: foundations of manufacturing management. McGraw-Hill-Irwin, New York (2000)
Johnson, H.: Lean accounting: To become lean, shed accounting©. Journal of cost management 20(1), 6–17 (2006)
Kaplan, R., Norton, D.: The balanced scorecard: translating strategy into action, 4th edn. Harvard Business School Press, Boston (1997)
Karmarkar, U.: Lot sizes, lead times and in-process inventories. Management Science 33(3), 409–418 (1987)
Karmarkar, U., Kekre, S., Kekre, S.: Lotsizing in multi-item multi-machine job shops. IIE transactions 17(3), 290–298 (1985a)
Karmarkar, U., Kekre, S., Kekre, S., Freeman, S.: Lot-sizing and lead-time performance in a manufacturing cell. Interfaces 15(2), 1–9 (1985b)
Koo, P.H., Bulfin, R., Koh, S.: Determination of batch size at a bottleneck machine in manufacturing systems. International Journal of Production Research 45(5), 1215–1231 (2007)
Kuehn, P., Siegen, G., Siegen, G.: Approximate analysis of general queuing networks by decomposition. IEEE Transactions Communicationson 27(1), 113–126 (1979)
Lee, H.: Aligning supply chain strategies with product uncertainties. California management review 44(3), 105–119 (2002)
Li Z, Xu X, Kumar A (2007) Supply Chain Performance Evaluation from Structural and Operational Levels. Emerging Technologies and Factory Automation pp 1131–1140
Little, J.: A proof for the queuing formula: L= λ W. Operations Research 9(3), 383–387 (1961)
Maskell, B., Kennedy, F.: Why do we need lean accounting and how does it work? Journal of Corporate Accounting & Finance 18(3), 59–73 (2007)
Mason-Jones, R., Naylor, B., Towill, D.: Lean, agile or leagile? Matching your supply chain to the marketplace. International Journal of Production Research 38(17), 4061–4070 (2000)
Maynard R (2008) Lean accounting. Financial Management pp 43–46
Van der Merwe A (2008) Debating the principles: Asking questions of lean accounting. Cost Accounting pp 29–36
Nahmias, S.: Production and operations analysis. McGraw-Hill Irwin, Boston (2005)
Naylor, B., Naim, M., Berry, D.: Leagility: integrating the lean and agile manufacturing paradigms in the total supply chain. International Journal of Production Economics 62(1-2), 107–118 (1999)
Neely, A.: The performance measurement revolution: why now and what next? International Journal of Operations and Production Management 19, 205–228 (1999)
Neely, A., Mills, J., Platts, K., Richards, H., Gregory, M., Bourne, M., Kennerley, M.: Performance measurement system design: developing and testing a process-based approach. International Journal of Operations and Production Management 20(10), 1119–1145 (2000)
Rabta, B.: A review of decomposition methods for open queueing networks. In: Reiner, G. (ed.) rapid modelling for increasing competitiveness: tools and mindset, Springer, London (2009)
Rabta B, Reiner G (2010) Batch size optimization by means of evolutionary algorithms and queuing network analysis. University of Neuchâtel, working paper
Rabta, B., Alp, A., Reiner, G.: Queueing networks modelling software for manufacturing. In: Reiner, G. (ed.) Rapid modelling for increasing competitiveness: tools and mindset, Springer, London (2009)
Reiner, G.: Customer-oriented improvement and evaluation of supply chain processes supported by simulation models. International journal of production economics 96(3), 381–395 (2005)
Reiner, G.: Rapid modelling for increasing competitiveness: tools and mindset. Springer, London (2009)
Reiner, G., Hofmann, P.: Efficiency analysis of supply chain processes. International Journal of Production Research 44(23), 5065–5087 (2006)
Santos, S., Belton, V., Howick, S.: Adding value to performance measurement by using system dynamics and multicriteria analysis. International journal of operations and production management 22(11), 1246–1272 (2002)
Shanthikumar, J., Ding, S., Zhang, M.: Queueing theory for semiconductor manufacturing systems: A survey and open problems. IEEE Transactions on Automation Science and Engineering 4(4), 513–522 (2007)
Silver, E.: Process management instead of operations management. Manufacturing & Service Operations Management 6(4), 273–279 (2004)
Silver, E., Pyke, D., Peterson, R., et al.: Inventory management and production planning and scheduling. Wiley, New York (1998)
Slack, N., Lewis, M.: Operations strategy, 2nd edn. Prentice Hall international, Harlow (2007)
Stalk, J., Hout, T.: Competing against time: how time-based competition is reshaping global markets. Free Press, New York (1990)
Suri R (1998) Quick response manufacturing: a companywide approach to reducing lead times. Productivity Pr
Suri, R., Sanders, J., Kamath, M.: Performance evaluation of production networks. In: Kan, S., Zipkin, P. (eds.) Logistics and production inventory (Handbooks oin operations research and management science), vol. 4, Elsevier Science Publishers B.V., Amsterdam (1993)
de Treville, S., van Ackere, A.: Equipping students to reduce lead times: The role of queuing-theory-based modeling. Interfaces 36(2), 165 (2006)
de Treville, S., Shapiro, R., Hameri, A.: From supply chain to demand chain: the role of lead time reduction in improving demand chain performance. Journal of Operations Management 21(6), 613–627 (2004)
de Treville, S., Hoffrage, U., Petty, J.: Managerial decision making and lead times: the impact of cognitive illusions. In: Reiner, G. (ed.) Rapid Modelling for Increasing Competitiveness: Tools and Mindset, Springer, London (2009)
Vaughan, T.: Lot size effects on process lead time, lead time demand, and safety stock. International Journal of Production Economics 100(1), 1–9 (2004)
Whitt, W.: The queueing network analyzer. Bell System Technical Journal 62(9), 2779–2815 (1983)
Yang, B., Geunes, J.: Inventory and lead time planning with lead-time-sensitive demand. IIE Transactions 39(5), 439–452 (2007)
Zheng, P., Lai, K.: A rough set approach on supply chain dynamic performance measurement. Springer, Berlin (2008)
Zipkin, P.: Models for design and control of stochastic, multi-item batch production systems. Operations Research 34(1), 91–104 (1986)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2011 Springer-Verlag London Limited
About this paper
Cite this paper
Gläßer, D., Rabta, B., Reiner, G., Alp, A. (2011). Evaluation of the Dynamic Impacts of Lead Time Reduction on Finance Based on Open Queueing Networks. In: Reiner, G. (eds) Rapid Modelling and Quick Response. Springer, London. https://doi.org/10.1007/978-1-84996-525-5_11
Download citation
DOI: https://doi.org/10.1007/978-1-84996-525-5_11
Published:
Publisher Name: Springer, London
Print ISBN: 978-1-84996-524-8
Online ISBN: 978-1-84996-525-5
eBook Packages: EngineeringEngineering (R0)