About E.Kasey KasemodelHe began his computer career in Milwaukee at Inland Steel/Composite Panels Division, by writing regression models on a TI-59 and then on mainframe using a language called PL/I and SAS. This was back when writing code required some physical effort. The single printer was located about 1/2 mile from the manufacturing office where the one mainframe terminal for the plant floor was located.
Perhaps his study of mechanical engineering fueled his passion for writing analytical software that began at Inland Steel. Based on his computer experience and process oriented approach, he was hired by a structural plastics company in the Dallas/Fort Worth area to automate test reporting. There he developed software programs to generate product certifications for the FAA, commercial and military aviation OEMs.
After years of immersion within the US aerospace and high-tech marine industries, he moved to France to work with a manufacturer of structural core materials for EU-based aerospace and high-tech marine manufacturers.
He developed engineering software to analyze composite structures (epoxy, carbon fiber, graphite, PVC and Nomex sandwich cores) for use within commercial, military vehicles and high-tech racing yachts.
He was part of the team that developed a finite element analysis program called STRUSAP. Kase designed and was the lead developer of COPAN/II, a composite panel analysis software program that was sold to naval architects along with the US Department of Defense (NAVSEA Combat Systems).
Feeling the call of his entrepreneurial spirit, he became part of a tech start-up that created The Personal Companion, a voice-activated, interactive system that utilized leading edge voice recognition technology.
Leading the news aggregation group, Kase designed one of the first "bots" to automatically gather daily news from Gannett New Media based on how frequently users viewed certain articles.
The company received national recognition in addition to The Personal Companion being voted the Michigan Technology Council Innovation of the Year. Twenty years leater, Siri and Alexa were born.
As voice recognition became more viable, new opportunity was discovered in auto manufacturing. Initially, Kase provided technical consulting and network design services to Mazda Motors and helped form their IT group that supported vehicle assembly operations. This included a variety of projects from wiring the plant floor with fiber optic cable, configuring Cisco routers to writing software to achieve compliance or improve vehicle quality. He was then hired into Mazda Systems Services, reporting to the plant manager.
The game-changer during the Mazda era was QMIS (Quality Management Info System), an assembly line voice-recognition project, co-built with Allen Bradley/Rockwell Automation, that replaced pens and clipboards with a belt-worn, data collection, voice input system. This project reduced QC turn-around time from 2 shifts to 5 minutes. QMIS was nominated to the Smithsonian Computerworld Awards where it placed in the top 3 in the factory floor automation division.
Kase recognized the value in the delivery of real-time production counts and alerts to alphanumeric pagers so management could react to quality issues in minutes, not hours. Long before the term "texting" was coined, Kase started a trend that put 4000+ alpha-pagers into the Ford plants to broadcast production states. Kase was promoted to a position at Vehicle Operations in Dearborn, MI as IT Business Manager for North American Stamping operations.
While at the Ford Woodhaven plant as a CIM (Computer Integrated Manufacturing) manager, Kase spear-headed and secured funding for the development team that created a logistics inventory/scheduling system called JEDI (Just-In-Time Execution Distribution Initiative). This project was the ultimate manufacturing bot, acquiring data from multiple disparate corporate systems for the purpose of making critical decisions to schedule production. This was designed and written by a covert team within the Ford Science Research Lab, as it was vehemently supported by plant scheduling personnel and plant management. JEDI replaced i2 Production Scheduler, a multi-million dollar project that in almost a year of "installation" was never used to schedule a single part.
JEDI was deployed and eventually was nominated and won the annual Henry Ford Technology Award. After 10+ years, this application continued to provide Ford stamping plants with a tool that mostly eliminated premium freight due to scheduling glitches.
After 15 years of IT development and management at Mazda and Ford Motor Company, Kase left to form a consulting firm that has managed hundreds of IT projects ranging from a logistic freight systems that optimized deliveries, to an ERP cloud-based manufacturing enterprise-class business intelligence platform.
Kase continues to be focused on integrating modern technologies into cloud-based systems and marketplaces.
In 2018, Kase designed and produced an application called NAILCAR, an AI-based system that monitors, alerts and predicts trends to improve and accelerate sound business decisions in a variety of tech vertical markets. In 2019, Kase was the CTO of a Milwaukee start-up that produced a local services marketplace app.
Kase has decades of experience in the areas of cyber security, systems design, business intelligence, corporate behavioral science, intellectual property management, and software engineering. This has allowed him to enjoy many years of assisting small businesses and multi-national corporations helping them gain improved positions from data analysis to enterprise-wide system efficiencies.
A native of Wauwatosa, WI, Kase ended up in Michigan after his return from France. He raised a family in Ann Arbor and played golf, foosball, ran half-marathons and occasionally cheered for the Wolverines. Kase returned to Wisconsin in 2014 and now lives in Mequon where he continues to design and build data automation systems, pump iron, play golf and is always on the lookout for a good game of foosball. Rooting for the Wolverines, not so much.
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