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NPI: A How To Guide for Engineers & Their Leaders
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Leading from the Front
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Marcel Tremblay: The Olympic Mindset & Engineering Leadership
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Anurag Gupta: Framework to Accelerate NPI
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Kyle Wiens on Why Design Repairability is Good for Business
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Nathan Ackerman on NPI: Do The Hard Thing First
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JDM Operational Excellence in NPI
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Building the Team
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Quality is Set in Development & Maintained in Production
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3 Lessons from Tesla’s Former NPI Leader
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Maik Duwensee: The Future of Hardware Integrity & Reliabilitypopular
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Reject Fake NPI Schedules to Ship on Time
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Leadership Guidance for Failure to Meet Exit Criteria
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Screws & Glue: Getting Stuff Done
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Choosing the best CAD software for product design
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Screws vs Glues in Design, Assembly, & Repair
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Best Practices for Glue in Electronics
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A Practical Guide to Magnets
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Inspection 101: Measurements
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A Primer on Color Matching
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OK2Fly Checklists
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Developing Your Reliability Test Suite
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Guide to DOEs (Design of Experiments)
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Ten Chinese phrases for your next build
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NPI Processes & Workflows
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Production: A Primer for Operations, Quality, & Their Leaders
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Leading for Scale
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Proven Strategies for Collaborating with Contract Manufacturers
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Greg Reichow’s Manufacturing Process Performance Quadrants
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8D Problem Solving: Sam Bowen Describes the Power of Stopping
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Cut Costs by Getting Your Engineers in the Field
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Garrett Bastable on Building Your Own Factory
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Oracle Supply Chain Leader Mitigates Risk with Better Relationships
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Brendan Green on Working with Manufacturers
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Surviving Disaster: A Lesson in Quality from Marcy Alstott
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Ship It!
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Production Processes & Workflows
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Failure Analysis Methods for Product Design Engineers: Tools and Techniques
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Thinking Ahead: How to Evaluate New Technologies
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How to Buy Software (for Hardware Leaders who Usually Don’t)
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Adopting AI in the Aerospace and Defense Electronics Space
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Build vs Buy: A Guide to Implementing Smart Manufacturing Technology
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Leonel Leal on How Engineers Should Frame a Business Case for Innovation
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Saw through the Buzzwords
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Managed Cloud vs Self-Hosted Cloud vs On-Premises for Manufacturing Data
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AOI, Smart AOI, & Beyond: Keyence vs Cognex vs Instrumentalpopular
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Visual Inspection AI: AWS Lookout, Landing AI, & Instrumental
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Manual Inspection vs. AI Inspection with Instrumentalpopular
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Electronics Assembly Automation Tipping Points
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CTO of ASUS: Systems Integrators for Manufacturing Automation Don't Scale
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ROI-Driven Business Cases & Realized Value
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One of the biggest challenges facing visionaries and leaders looking to invest in technology is filtering through all of the noise -- both externally and internally.
External noise makes it difficult to understand even what a potential company or technology can really offer you -- it sounds like technobabble on an episode of Star Trek.
Internal noise comes from whatever your management is reading about on Twitter or in the news that day: How will you incorporate large language models (LLMs like ChatGPT) into our operations? What about AI? When are we going to get some AI?
MidJourney's artistic interpretation of the prompt "buzzword technobabble"
One of the most important steps in investigating and considering new technologies to amplify and optimize your process is to push through the internal noise to focus on the business opportunity (improve margins to increase profitability or EBITDA) and its associated key metrics (such as yield, throughput, etc), and through the external noise to match a technology or investment that can actually move those key metrics (such as automation, data team, AI, etc). This chapter will help you do that by covering some of the buzzy technologies you may be asked about -- and connecting them to the core KPIs they can move in the business.