Skip to main content

Evaluation of the Dynamic Impacts of Lead Time Reduction on Finance Based on Open Queueing Networks

  • Conference paper
  • First Online:
  • 1074 Accesses

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

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   169.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD   219.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

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)

    Article  Google Scholar 

  • Beamon, B.: Measuring supply chain performance. International journal of operations and production management 19(3), 275–292 (1999)

    Article  Google Scholar 

  • Bodie, Z., Kane, A., Marcus, A.: Essentials of investments, 5th edn. McGraw-Hill Irwin, New York (2003)

    Google Scholar 

  • 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)

    MATH  Google Scholar 

  • 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)

    Article  Google Scholar 

  • Croom S (2009) Introduction to research methodology in operations. In: Karlsson C (ed) Researching operations management, 1st edn, Routledge, New York

    Google Scholar 

  • Ghalayini, A., Noble, J.: The changing basis of performance measurement. International Journal of Operations and Production Management 16(8), 63–80 (1996)

    Article  Google Scholar 

  • Govil, M., Fu, M.: Queueing theory in manufacturing: a survey. Journal of Manufacturing Systems 18(3), 214–240 (1999)

    Article  Google Scholar 

  • 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)

    Article  Google Scholar 

  • 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)

    Article  Google Scholar 

  • Haque, L., Armstrong, M.: A survey of the machine interference problem. European Journal of Operational Research 179(2), 469–482 (2006)

    Article  Google Scholar 

  • 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)

    Article  Google Scholar 

  • Hofmann, P., Reiner, G.: Drivers for improving supply chain performance: an empirical study. International Journal of Integrated Supply Management 2(3), 214–230 (2006)

    Article  Google Scholar 

  • Hopp, W., Spearman, M.: Factory physics: foundations of manufacturing management. McGraw-Hill-Irwin, New York (2000)

    Google Scholar 

  • Johnson, H.: Lean accounting: To become lean, shed accounting©. Journal of cost management 20(1), 6–17 (2006)

    Google Scholar 

  • Kaplan, R., Norton, D.: The balanced scorecard: translating strategy into action, 4th edn. Harvard Business School Press, Boston (1997)

    Google Scholar 

  • Karmarkar, U.: Lot sizes, lead times and in-process inventories. Management Science 33(3), 409–418 (1987)

    Article  MATH  MathSciNet  Google Scholar 

  • Karmarkar, U., Kekre, S., Kekre, S.: Lotsizing in multi-item multi-machine job shops. IIE transactions 17(3), 290–298 (1985a)

    Article  Google Scholar 

  • Karmarkar, U., Kekre, S., Kekre, S., Freeman, S.: Lot-sizing and lead-time performance in a manufacturing cell. Interfaces 15(2), 1–9 (1985b)

    Article  Google Scholar 

  • 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)

    Article  MATH  Google Scholar 

  • Kuehn, P., Siegen, G., Siegen, G.: Approximate analysis of general queuing networks by decomposition. IEEE Transactions Communicationson 27(1), 113–126 (1979)

    Article  MATH  Google Scholar 

  • Lee, H.: Aligning supply chain strategies with product uncertainties. California management review 44(3), 105–119 (2002)

    Google Scholar 

  • Li Z, Xu X, Kumar A (2007) Supply Chain Performance Evaluation from Structural and Operational Levels. Emerging Technologies and Factory Automation pp 1131–1140

    Google Scholar 

  • Little, J.: A proof for the queuing formula: L= λ W. Operations Research 9(3), 383–387 (1961)

    Article  MATH  MathSciNet  Google Scholar 

  • 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)

    Article  Google Scholar 

  • 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)

    Article  Google Scholar 

  • Maynard R (2008) Lean accounting. Financial Management pp 43–46

    Google Scholar 

  • Van der Merwe A (2008) Debating the principles: Asking questions of lean accounting. Cost Accounting pp 29–36

    Google Scholar 

  • Nahmias, S.: Production and operations analysis. McGraw-Hill Irwin, Boston (2005)

    Google Scholar 

  • 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)

    Article  Google Scholar 

  • Neely, A.: The performance measurement revolution: why now and what next? International Journal of Operations and Production Management 19, 205–228 (1999)

    Article  Google Scholar 

  • 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)

    Article  Google Scholar 

  • 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)

    Google Scholar 

  • Rabta B, Reiner G (2010) Batch size optimization by means of evolutionary algorithms and queuing network analysis. University of Neuchâtel, working paper

    Google Scholar 

  • 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)

    Google Scholar 

  • 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)

    Article  Google Scholar 

  • Reiner, G.: Rapid modelling for increasing competitiveness: tools and mindset. Springer, London (2009)

    Book  Google Scholar 

  • Reiner, G., Hofmann, P.: Efficiency analysis of supply chain processes. International Journal of Production Research 44(23), 5065–5087 (2006)

    Article  MATH  Google Scholar 

  • 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)

    Article  Google Scholar 

  • 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)

    Article  Google Scholar 

  • Silver, E.: Process management instead of operations management. Manufacturing & Service Operations Management 6(4), 273–279 (2004)

    Article  Google Scholar 

  • Silver, E., Pyke, D., Peterson, R., et al.: Inventory management and production planning and scheduling. Wiley, New York (1998)

    Google Scholar 

  • Slack, N., Lewis, M.: Operations strategy, 2nd edn. Prentice Hall international, Harlow (2007)

    Google Scholar 

  • Stalk, J., Hout, T.: Competing against time: how time-based competition is reshaping global markets. Free Press, New York (1990)

    Google Scholar 

  • Suri R (1998) Quick response manufacturing: a companywide approach to reducing lead times. Productivity Pr

    Google Scholar 

  • 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)

    Google Scholar 

  • de Treville, S., van Ackere, A.: Equipping students to reduce lead times: The role of queuing-theory-based modeling. Interfaces 36(2), 165 (2006)

    Article  Google Scholar 

  • 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)

    Article  Google Scholar 

  • 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)

    Google Scholar 

  • 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)

    Article  Google Scholar 

  • Whitt, W.: The queueing network analyzer. Bell System Technical Journal 62(9), 2779–2815 (1983)

    Google Scholar 

  • Yang, B., Geunes, J.: Inventory and lead time planning with lead-time-sensitive demand. IIE Transactions 39(5), 439–452 (2007)

    Article  Google Scholar 

  • Zheng, P., Lai, K.: A rough set approach on supply chain dynamic performance measurement. Springer, Berlin (2008)

    Google Scholar 

  • Zipkin, P.: Models for design and control of stochastic, multi-item batch production systems. Operations Research 34(1), 91–104 (1986)

    Article  MATH  MathSciNet  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Dominik Gläßer .

Editor information

Editors and Affiliations

Rights and permissions

Reprints 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)

Publish with us

Policies and ethics