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    James L. Kutney

    Fellowship Student
    Honeywell/University of Missouri
    Cleveland, MO, United States

    James L. Kutney

    Supply Chain & Microelectronics Assurance Leader
    Fellowship Student – Honeywell FM&T / University of Missouri

    James Kutney brings more than three decades of global supply chain and process optimization leadership to the semiconductor industry, culminating in the completion of his M.S. in Industrial Engineering at age 62 from the University of Missouri. His career spans defense electronics, energy, and advanced manufacturing, where he has consistently delivered transformative results across procurement, supplier management, and microelectronics assurance.

    At Honeywell FM&T, James advanced through roles in materials science, program management, and technical fellowship, applying AI-driven risk models to microelectronic assembly and chiplet assurance. His work streamlined electronics sourcing, cutting procurement cycles from 3,600+ to fewer than 200 purchase orders annually, while achieving hundreds of millions in negotiated savings and improving quality, delivery, and reliability.

    Previously, James held senior roles at BP, Chevron, IHI, Babcock & Wilcox, and Black & Veatch, managing multi-billion-dollar energy and infrastructure projects across the U.S., Africa, and Asia. His leadership included overseeing procurement and QC for $2.7 billion in power plant packages—delivered on time and on budget—and reengineering BP’s $5 billion South Africa supply chain team to world-class performance.

    James’s master’s thesis, Microelectronic Capacity, Supply, and Assurance: Risk Quantification Framework, surveys the manufacturing lifecycle of microelectronics—wafer prep, photolithography, chiplet assembly, packaging, and testing—against industry standards (JEDEC, MIL-STD, IEC, IEEE, AEC, IPC, UCIe, DFARS). His research highlights the geopolitical, policy, and technological risks threatening semiconductor assurance, and introduces artificial intelligence with human-in-the-loop frameworks to minimize disruptions, shortages, and sabotage in critical supply chains. By combining 40 years of industry experience with AI research, James demonstrates the practical and strategic value of large language models in evaluating gaps in standards, comparing testing methodologies, and supporting collaborative decision-making.

    Education

    M.S., Industrial Engineering (Supply Chain) – Univ. of Missouri, Columbia (2025)

    MBA, Finance – Case Western Reserve University

    B.S., Chemistry – Wright State University

    Certifications & Interests

    Six Sigma Black Belt | PMP (in progress)

    Specialization in microelectronics assurance and SMT optimization

    Presentation(s):