One aspect of creating a new product or system is the sourcing of parts, components, and materials.
Gone are the days of your organization providing every element of the final product. Henry Ford’s supply chain for early Ford automobiles includes their own forests, rubber plantations, and iron ore mines. [Gelderman, 1981]
We increasingly rely on the supply chain to create the necessary parts for the design’s functionality. Then to continue to supply those same parts for decades, in some cases.
As of 2006, approximately 3% of electronic components become obsolete. [Q Star, 2006]
If you happen to be using one of these parts, you will need to find a viable replacement. In some industries, such as the military equipment, aerospace, and solar power industries, systems may have an expected operating life of 30 years or more. Plus, organizations may manufacture equipment according to design specifications established decades ago.
Obsolescence isn’t limited to electronic components. Mechanical and software elements may likewise require obsolescence management.
Consider the risk of obsolescence during parts selection
According to Jackson, et.al. [Jackson, 1999] the parts selection process during the application-dependent assessment includes four equally important considerations:
- Performance assessment “can work”
- Reliability assessment “won’t fail”
- Assembly assessment “can make”
- Lifecycle obsolescence assessment “can sustain”
Considerations include the vendor’s plans to continue making the part.
Plus the consideration of the vendor’s ability to remain in business. Beyond the specific part and vendor, the selection process should also consider the availability of the same part or very similar parts manufactured by other vendors in the industry.
Manufacturers of parts continue to create improved parts, new functionality and tend to cater the markets they serve. Over time manufacturers decide to discontinue manufacturing specific parts due to:
- Rapid changes in technology (components, materials, etc.)
- Uneconomical production requirements
- Environmental or safety requirements,
- Limited availability of items
[Pobiak, et.al. 2014]
Manufacturing and maintenance requirements
Industrial equipment and aircraft are examples of systems that remain in production for decades after the initial design phase.
Securing parts for production increases in difficulty as more parts become obsolete. The cost of finding replacement parts to maintain the system functionality may include:
- Searching for suitable candidate parts/vendors
- Verification and validation of replacement parts
- Possible redesign to accommodate loss of specific parts
Similar issues arise even after production ends when providing spare parts for system maintenance. As the electronics industry moved to lead-free solder, accommodating regulatory requirements, the ability to procure spare parts only found using the now restricted materials accelerated the obsolescence of parts.
Furthermore, electronic assembly vendors ceased or limited production using the restricted materials in part to avoid contamination and in part due to economic reasons.
As the demand for tin-lead solder based assemblies dwindles it is not ecumenical to maintain equipment ready to operate using tin-lead solder.
Forecasting parts obsolescence
When selecting parts for a new product, that ability to foresee obsolescence is difficult.
The economy, technology, and regulations are examples of some of the forces that cause unforeseen parts obsolescence. Being able to identify when a specific part will become obsolete as early as possible permits a wider range of solutions, plus additional time to find and implement a solution.
Sandborn, et al. Used a data mining approach modeling the history of part obsolescence for specific electronic technologies. The paper explores fitting the dates of obsolescence in order to extrapolate to future obsolescence dates. [Sandborn, 2007]
Li et.all proposes a proportional hazard model using indicators of
- Lead time increases
- Price increases
- Cycle time increases
- Throughput decreases
To indicate an increased risk of part obsolescence. [Li, 2016] The model provides a means to monitor the change is the risk of obsolescence permitting longer lead time to accommodate the loss of specific part availability.
Obsolescence is not new.
In the 1940s, the utility industry was experiencing an obsolescence problem. [Bonbright, 1941] The pace of technology advancement along with shorter design and product lifecycle, plus the ongoing regulatory limitation of hazardous material, has only accelerated the pace of part obsolescence.
Recognizing the issue and addressing it as early as possible creates a wider range of solutions. Beyond simple planning and monitoring, there are various models to assist in predicting obsolescence.
In a future article, we’ll discuss the various options available to continue production or maintenance activities when facing parts obsolescence.
Gelderman, Carol W. 1981. Henry Ford: The Wayward Capitalist. New York: Dial Press.
Q Star, “Approximately 3% of the global pool of electronic components goes obsolete every month,” Tech. Rep., 2006 [Online]. Avail- able: http://www.qtec.us/Products/QStar_Introduction.htm
Jackson, Margaret, Peter Sandborn, Michael Pecht, Chantal Hemens-Davis, and Pierre Audette. 1999. “A Risk-Informed Methodology for Parts Selection and Management.” Quality and Reliability Engineering International 15 (4): 261-271.
Pobiak, T. G., Mazzuchi, T. A. and Sarkani, S. (2014), Creating a Proactive Obsolescence Management System Framework through the Systems Engineering Continuum. Syst. Engin., 17: 125–139.
J.C. Bonbright, Major controversies as to the criteria of reasonable public utility rates, Amer Econ Rev 30(5) (1941), 379–389.
Sandborn, P. A., F. Mauro, and R. Knox. 2007. “A Data Mining Based Approach to Electronic Part Obsolescence Forecasting.” IEEE TRANSACTIONS on COMPONENTS and PACKAGING TECHNOLOGIES 30 (3): 397-401.
Li, X., Dekker, R., Heij, C. and Hekimoğlu, M. (2016), Assessing End-Of-Supply Risk of Spare Parts Using the Proportional Hazard Model. Decision Sciences, 47: 373–394. doi: 10.1111/deci.12192
Part Selection Process and Reliability (article)