Many U.S. manufacturing operations are data rich, knowledge poor, and as a result, operating with a constrained decision making process, even in operations using sophisticated modeling and control technologies. Smart Manufacturing (“SM”) systems that integrate manufacturing intelligence in real-time across an entire production operation are rare in large companies, and virtually non-existent in small and medium size organizations.
In U.S. industries, energy is frequently the second largest operating cost; approximately 30% of the energy delivered to a manufacturing site is lost as waste heat. Unfortunately, a cost effective infrastructure to integrate manufacturing intelligence in real-time across an entire production operation does not currently exist, and business decisions are typically implemented with incomplete knowledge of the relationship between product output and energy use.
The overall objectives of Project Smart Manufacturing are to design and demonstrate an open, common platform that enables data, modeling, and simulation technologies for active, real-time decisions to manage energy use in conjunction with production performance metrics, and to use the platform to establish how optimization of energy productivity as a key driver in business decisions can be applied across many U.S. manufacturing companies.
Using two energy-intensive plants as test beds (steam methane reforming and forging/machining/ heat treatment) will validate the approach proposed in this project. Achieving the objective of Project Smart Manufacturing requires development of the Smart Manufacturing Platform (“SM Platform”). The SM Platform is an innovative approach that allows manufacturing organizations to assemble new management systems at much lower cost of deployment than is required today and extract new levels of intelligence from their operation to optimize energy productivity.
A broad-based energy productivity metric and application toolkit in the SM Platform will allow manufacturers to select the key variables, weighting factors, and ranges of measurement best suited to a particular process or production operation.The energy productivity metric will be integrated with real-time information collected across all process steps and used to provide comparisons of energy productivity against theoretical potential, practical capability, and actual performance.