Large Pharmaceutical Company Averts Failures, Saves Millions
Challenge: At a large-scale pharmaceutical manufacturing location, large chillers and compressors are critical equipment infrastructure. In spite of all six sigma efforts, failures still caused enormous losses. Aging equipment, increasing energy usage over time, higher maintenance (where 35% is corrective and 65% preventive), and inadequate equipment health status reporting contributed to the problem.
Solution: The equipment now warns of impending failures and advises when it should be maintained.
Benefit: Mtell predictive-scheduling using advance machine learning reversed the situation, providing sufficient notice for orderly, rapid problem correction at the lowest cost. A direct link to the maintenance system also increased operator involvement. The net result is a dramatic improvement in overall production valued at $millions per year.