Benefits of Implementing Automated Costing in a Small Machine Shop: A Case Study

Authors

  • Benito A Gonzalez Manufacturing Engineering University of Texas-Pan American Edinburg, TX
  • Alley C Butler Manufacturing Engineering University of Texas-Pan American Edinburg, TX

DOI:

https://doi.org/10.37266/ISER.2013v1i2.pp132-143

Abstract

Knowledge based cost estimating systems are available, but is there a lower limit to their applicability in an industrial environment?  This paper answers this question by examining a knowledge based cost estimating expert system application in a small machine shop.  Differences between the traditional experienced-based system currently employed and the automated system are studied.  Data is gathered to analyze time effectiveness, accuracy, and payback of the software.  Data from seventy part models is recorded to study the time experiment and data from fifty part models is used to study accuracy and consistency.

The results indicate that the software is faster than traditional quoting systems; however, the payback point is high. Also, results show that the software has a smaller average time to manufacture percent difference between the automated system and the actual time to manufacture (TTM) compared to the percentage difference between the traditional TTM and actual TTM. Standard deviation for the automation is also less, implying better consistency.  As a result, the attractiveness of the automated system in the limiting case of a small machine shop rests with significantly improved accuracy and consistency rather than payback.

 

References

Brammall, D.G., McKay, K.R., Rogers, B.C., Chapman, P., Cheung, W.M. and Maropoulos, P.G. (2003). Manufacturability analysis of early product designs. Int. J. Computer Integrated Manufacturing, Vol 16, No. 7-8, 501-508.

Cakir, M.C. and Cavdar, K. (2006). Development of a knowledge-based expert system for solving metal cutting problems. Materials and Design, Vol 27, 1027-1034.

Chang, P.C., Lin, J.J., Dzan, W.Y. (2010). Forecasting of manufacturing cost in mobile phone products by case-based reasoning and artificial neural network models. Journal of Intelligent Manufacturing, Vol 23:3, 517-531.

Culler, D.E. and Burd, W. (2007). A framework for extending computer aided process planning to include business activities and computer aided design and manufacturing (CAD/CAM) data retrieval. Robotics and Computer-Integrated Manufacturing, Vol 23, 339-350.

Daabub, A.M. and Abdalla, H.S. (1999). A computer-based intelligent system for design for assembly. Computers & Industrial Engineering, Vol 37, 111-115.

Duverlie, P. and Castelain, J.M. (1999). Cost estimation during design step: parametric method versus case based reasoning method. International Journal of Advanced Manufacturing Technology, Vol 15, 895-906.

Ficko, M., Drstvensek, I., Brezocnik, M., Balic, J. and Vaupotic, B. (2005). Prediction of total manufacturing costs for stampingg tool on the basis of CAD-model of finished product. Journal of Materials Processing Technology, Vol 164-165, 1327-1335.

Fisher, J., Koch, R., Hauschutte, K.B., Schmidt, B., Jakuschona, K. and Szu, K. (1994). An object-oriented approach for activity-based cost estimation in the engineering in the engineering process. Methodologies; techniques, and tools for design development, Vol 64:5, 453-461.

Garcia C, A., Ruiz M, B., Lopez C, J.L. and Gonzalez C, I. (2009). A review of conventional and knowledge based systems for machining price quotation. Journal of Intelligent Manufacturing, Vol 22:6, 823-841.

Gayretli, A., and Abdalla, H.S. 1999. An object-oriented constraints-based system for concurrent product development. Robotics and Computer-Integrated Manufacturing, Vol 15, 133-144.

Gonzalez, B. (2012). “A Case Study of Financial Feasibility for Automated Costing in a Small Machine Shop,” MS Thesis, University of Texas-Pan American, Edinburg, TX.

Humphreys, P., McIvor, R. and Huang, G. (2002). An expert system for evaluating the make or buy decision. Computers & Industrial Engineering, Vol 42, 567-585.

Kingsman, B. and de Souza, A. (1997). A knowledge-based decision support system for cost estimation and pricing decisions in versatile manufacturing companies. International Journal of Production Economics, Vol 53:2, 119-139.

Koltai, T., Lozano, S., Guerrero, F. and Onieva, L. (2000). A flexible costing system for flexible manufacturing system using activity based costing. International Journal of Production Research, Vol 38:7, 1615-1630.

Montgomery, D. C. and Runger, G. C. (2006). Applied Statistics and Probability for Engineers. John Wiley & Sons, 4th Edition. New York. 375-376.

Needy, K.L., Billo, R.E. and Warner, R.C. (1998). A cost model for the evalutation of alternative cellular manufacturing configurations. Computers & Industrial Engineering, Vol 34:1. 119-134.

Ping, L., Yongtong, H., Bode, J. and Shouju, R. (1996). Multi-agent system for cost estimation. Computers & Industrial Engineering, Vol 31:3/4, 731-735.

Sanders, D., Tan, Y.C., Rogers, I. and Tewkesbury, G.E. (2009). An expert system for automatic design-for-assembly. Journal of Assembly Automation, Vol 29:4, 378-388.

Sharma, R. and Gao, J.X. (2007). A knowledge-based manufacturing and cost evaluation system for product design/re-design. International Journal of Advanced Manufacturing Technology, Vol 33. 856-865.

Shehab, E.M. and Adballa, H.S. (2001). Manufacturing cost modelling for concurrent product development. Robotics and Computer Integrated Manufacturing, Vol 17, 341-353.

Shehab, E.M. and Adballa, H.S. (2006). A cost-effective knowledge-based reasoning system for design for automation. Journal Engineering Manufacture, Vol 220 Part B, 1-15.

Sood, S. and Wright, P.K. (1993). Process planning: a review. Intelligent Concurrent Design: Fundamentals, Methodology, Modeling and Practice ASME, Vol 66, 45-54.

Zha, X.F. and Lim, S.Y.E. (2000). Assembly/disassembly task planning and simulation using expert Petri nets. International Journal of Production Research, Vol 38:15, 3639-3676.

Zha, X.F., Du, H.J. and Qiu, J.H. (2001). Knowledge-based approach and system for aseembly_oriented design, Part II: the system implementation. Engineering Applications of Artificial Intelligence, Vol 14, 239-254.

Published

2013-11-01

How to Cite

Gonzalez, B. A., & Butler, A. C. (2013). Benefits of Implementing Automated Costing in a Small Machine Shop: A Case Study. Industrial and Systems Engineering Review, 1(2), 132-143. https://doi.org/10.37266/ISER.2013v1i2.pp132-143