Combined Part and Product Views for Sourcing Optimization


The cost model presented below was developed for projects C12-25, C13-25, and C13-25 within the Center for Advanced Life Cycle Engineering (CALCE) at the University of Maryland, College Park. The focus of the primary cost model is the evaluation of the effect of two mitigating strategies, buffering and second sourcing, associated with supplier specific disruptions.


Project C12-25 Background

In the C12-25 project a model was developed that incorporates the evaluation of buffering and second sourcing strategies, defined in the key terms section below, associated with sourcing parts. The resulting model is capable of forecasting the number of parts in inventory, demanded, and backordered. Using the forecasted parts counts, the penalty costs are assessed and included within the cumulative cost of ownership of the part.

Project C13-25 Background

In the C13-25 project we extended the part-centric total cost of ownership model (developed in project C12-25) to include:

1)    Product-level interface: An additional interface was added to the front end of the model in order to collect and utilize product-specific inputs. The following inputs in particular were divided by product: qualification/approval cost, penalty cost, demand as a function of time, and product priority.  The interface also allows the user to decide whether or not to include specific products in the analysis.

2)    Solution management shell: A central shell was instituted into the model in order to assess the effectiveness of multiple mitigation strategy combinations.  This shell allows for the determination of an optimum management strategy.

Other minor additions and edits were incorporated into the model (such as scrap costs and second-sourcing specific inputs) in the C13-25 project. User reassessment of the optimal sourcing mitigation strategy is accomplished by manually dividing the part-usage life into different assessment periods that can then be run individually within the simulator.

Project C14-25 Objective

The current model takes both the forecasted and actual part demand (as a function of time) from multiple products and allows for the determination of an optimal sourcing mitigation method. However, the model lacks a generalized output needed to guide management-level sourcing decisions. Starting with the model developed in projects C12-25 and C13-25 we will perform the following work:

1)    Incorporate the effect of inventory aging into the inherent buffering model. Existing maintenance models need to be explored in order to produce the most accurate cost calculations associated with long-term inventory storage.

2)    Explore the effect of human error on sourcing disruptions. Human error falls under all of the major disruption categories, however its cause is varied and its effect is difficult to predict. Further research into human error modeling is needed, as it is one of the most common causes of supply chain disruption.

3)    Develop a novel framework within the existing model that allows for the determination of the optimum disruption-mitigation strategies associated with a set of inputs. Trends observed from the outputs of sensitivity analyses performed in the part total cost of ownership model will hopefully allow for a reduction in necessary inputs.

Key Terms

  Second Sourcing: qualifying (and maintaining the qualification of) an alternative part supplier (or source) to ensure a redundancy in supply.


  Buffering: maintaining an inventory of parts equal to the forecasted part demand of a fixed future time period.


Release Date

Model & Documentation

                   Version Notes

Jan. 24, 2014

Version 2

    Software developed and tested with Microsoft Office 2013 on Windows 8 platform. Compatibility with other operating systems and programs is unknown

Dec. 20, 2012

Version 1

    Software developed and tested with Microsoft Office 2010 on Windows 8 platform. Compatibility with other operating systems and programs is unknown




V. Prabhakar and P. Sandborn, "A Part Total Cost of Ownership Model for Long Life Cycle Electronic Systems," International Journal of Computer Integrated Manufacturing, Vol. 25, Nos. 4-5, pp. 384-397, 2012.



For questions, please contact

Center for Advanced Life Cycle Engineering (CALCE)

University of Maryland-College Park

Last Edited: Jan. 23, 2014

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