The chemical manufacturing environment is filled with thousands of missed signals, where providing the right type of analyzed data to the right person, at the right time, can reduce out of spec product, minimize equipment downtime, and improve raw material utilization. After having success using Statistical Process Control at various sites, Albemarle wanted to scale the success across their global enterprise using Asset Framework (AF), along with their analytics partners, Northwest Analytics & Sartorius-Stedim SIMCA, with Machine Learning. To escape pilot purgatory, Albemarle committed to training all Manufacturing Engineers as Super-Users within AF, SPC, and multivariate analytics. This widespread adoption of AI ("Albemarle Intelligence") ensures long-term sustainability, empowers the company's employees, and truly unlocks the value of information.
Speaker
Jonathan Alexander
Jonathan Alexander is the Manufacturing Data Analytics Leader within Albemarle s global Manufacturing Excellence team. He has held a variety of roles within Manufacturing, including an I&E Maintenance Engineer, Operations Engineer for both the Hydroprocessing Catalyst Plant in Bayport, TX and the Aluminum Alkyl plants in Pasadena, TX, and as a TICA Engineer (Technology Implementation for Competitive Advantage). In his current role, he has been focused on powering the potential of people by scaling AI (Albemarle Intelligence) and changing Albemarle s culture around Manufacturing Data Analytics, an integral part of their journey towards Digital Transformation. Mr. Alexander holds a Bachelor of Science in Electrical Engineering from Louisiana State University and a Masters in Business Administration from The University of Houston in Clear Lake.