Phillip Zulueta is a Consultant to Industry, Chairman SAE G-19 Counterfeit Electronic Parts Committee where he develops and teaches systems and methods to improve operational performance and business growth. He also consults in the area of counterfeit electronic parts risk mitigation and standards compliance for applications in U.S. DoD, aerospace, high-reliability, medical and the global electronics industry. He has also worked as Program Element Manager and Hardware Technology Engineering Assurance Manager, Jet Propulsion Laboratory where he led groups of up to 32 members in all lifecycle aspects of projects, tasks and respective operations. He utilized mixture of analysis, experience and judgment for managing the Electronics Packaging effort of the NASA Electronics Parts and Packaging (NEPP) Program. He also delivered key technical support to DLA Land and Maritime electronics supplier compliance audits.
He was also awarded SAE Aerospace Chair Award for Outstanding Leadership as Chair of the G-19 Counterfeit Electronic Parts Committee. He was also the Past-President, International Microelectronics and Packaging Society (IMAPS) Chairman, SAE International G-19 Committee. He has pursued BS Materials Engineering, Materials Engineering from California State University-Long Beach and Masters, Business Administration, Finance, Marketing from Pepperdine University.
Director of Business Development, Optimal Plus, Ltd. will present on "Securing your supply chain from counterfeit parts through real-time, electronic chip traceability" at the Symposium on Counterfeit Parts and Materials by CALCE and SMTA.
Within the past decade, there have been significant increases in awareness and methods to avoid and mitigate the incidence of counterfeit parts in the electronics supply chain; all while the counterfeit issue continues to increase and plague the industry with ever-increasing schemes to counter these noble methods. We have created and continue to develop industry standards that assist in these efforts, addressing everything from managing initial design effort, managing part obsolescence, selecting reliable suppliers, implementing systematic counterfeit detection methods, training/certifying personnel in these detection methods and have even explored and implemented questionable "downstream" taggant and trace technologies. We have framed all of these in a risk-based landscape that does not absolutely guarantee authenticity or whether all parts are new, unused or do not contain added/covert malicious code. Although these new procedures and requirements are important and are valuable examples of industry-best (and sometimes idealistic) practices, they are actually "incomplete" because they are generally based on events that we cannot control or in the case of detection, based on sampling or partial testing.
Consider the following to address the above dilemma: Many semiconductor manufacturers use a variety of physically unclone-able functions (PUFs) to uniquely identify chips. Traceability can already be achieved by use of a die/chip PUF, more commonly known as an "electronic chip ID" (ECID). The ECI¬D is a register that contains a unique identifier for an individual die. The data in that register cannot be modified and ensures die-level traceability with positive results that include: yield improvement; enhanced quality; and for the physical-minded and/or cybersecurity-minded, absolute traceability in the electronics supply chain. This concept has already been leveraged by semiconductor manufacturers to address manufacturing and quality improvements. IEEE 1149.1-2013, the "Standard for Test Access Port and Boundary-Scan Architecture", a current international standard, includes a method for “reading” ECIDs as part of the manufacturing test process. For those involved in the efforts against counterfeit, these unique identifiers could allow authentication by a supplier, and most importantly, allow the OEM, to leverage those identities to create "fingerprints" at higher levels (e.g., board, subassembly and system levels). Thus, reading the unique identity allows an OEM to validate chip authenticity (particularly for complex devices such as ASICs and processors) in the course of manufacturing their products. Also within the past decade, Optimal Plus (Optimal+) a global big data analytics provider, has been aggregating and analyzing data on semiconductor devices used in tens of thousands of semiconductor products (more than 35 billion semiconductor devices on behalf of its OCM customers in 2015, a 50 percent increase from 2014). This has resulted in the accumulation of unmatched operational knowledge and has led to the development of scores of automated rules used within semiconductor manufacturing operations that contribute to significant quality improvements and fewer defective chips shipped for use in next-generation devices. Optimal+ is in a unique position to leverage their capabilities and infrastructure to address the counterfeit electronic parts issue and seeks collaboration to form true electronic parts authentication solution(s). This presentation will: 1. Convey a possible scheme to address counterfeit electronic part/supply chain traceability issues using an OCM-programmed ECID. 2. Include discussion on a simple pre-assembly validation step (by a supplier, test service or OEM) that could be implemented as a first step of electronic part authentication. 3. Convey the creation of an OEM assembly log (as-built list with ECIDs) to check for duplication and allow electronic part verification of prior use. 4. Include a call to action.
Optimal+ is leading a paradigm shift away from the fragmented data approach of current test environments into a next-generation, high-performance solution for manufacturing operations that drives significant improvements in product yield, quality and productivity. The Optimal+ Semiconductor Operations Platform enables a comprehensive, transparent view into manufacturing operations that enables your company to make real-time, data-driven decisions. Their comprehensive solution generates invaluable intelligence that connects disconnected, global manufacturing sites into a unified source of information; a game-changing paradigm that stands alone in the decision support landscape.