The lack of a corporate part numbering system is a major gap in our business. Data from our product lifecycle management (PLM) systems indicates that our engineers located in different geographic design locations design an average of 300 parts each day. An enterprise part numbering system (PNS) will significantly improve the management of our company's ever-changing parts portfolio. It will have a significant impact on all aspects of our operations, including supply chain management, inventory management, part number duplication, design duplication efforts, design management, change management and component reuse. The main objective of any PNS is to assign a unique number to each of the components that we design and manufacture for a specific application. There are three different methods of part numbering systems widely used in the industry.1. Important (or smart) part numbers2. Semi-meaningful (or semi-intelligent) part numbers3. Non-significant (random) part numbers. In this report, I analyze the advantages and disadvantages of each method. The method we select cannot be easily changed in the future. Therefore, the method we choose will have a lasting impact on our business. Important Part Numbers The important part number method is the earliest form of numbering system. In this method, each character in the part number has a meaning describing an aspect of the component such as product line, raw material, color, size, etc. And an engineer can identify the component details from the part number. For example, the part number of our hydraulic spin on 12AT/50AT series filters will be constructed as shown in Figure 1. Figure 1One of the main advantages of large part numbers is that they provide all the signs. ..... middle of paper... ...h.ebscohost.com/login.aspx?direct=true&db=edselp&AN=0167541987900020&site=eds-liveBallard, G. (2000). Positive VS negative iteration in design, in Proceedings of the 8th Annual Conference of the International Group for Lean Construction (IGLC-8). Brighton, United Kingdom http://repository.binus.ac.id/2009-1/content/T0194/T019479288.pdf Arundacahawat, P., Roy, R. and Al-Ashaab, A. (nd). An analogy-based estimation framework for design redesign efforts. Journal of Intelligent Manufacturing, 24(3), 625-639. ^ Jorgensen, Barbara. (June 2005). ). The “greening” of the supply chain. Electronic Commerce, Volume 31, Issue 6, pp.29-30.http://proxy.ulib.csuohio.edu:2050/login?url=http://search.ebscohost.com/login.aspx?direct=true&db =edo&AN=18020280&site=eds-live