overview


by University of California-Berkeley researchers in a NAMRC 2012 paper (http://tinyurl.com/tp12pub66). New functional materials suited to fl exographic printing were developed and analyzed for use in manufacturing energy storage devices. Electrical performance of laser braze-welded aluminum- copper interconnects for assembly of lithium-ion battery cells is the subject of collaboration by University of Luxembourg and General Motors Global R&D researchers, published re- cently in the Journal of Manufacturing Processes; http://tinyurl. com/JMP-interconnects). The main focus of the work is on the effect of intermetallic compounds on the contact electrical re- sistance of the Al-Cu joint, the correlation between mechanical and electrical properties of the joint and the impact of the weld seam layout on the contact electrical resistance.


Photo courtesy Lawrence Berkeley National Laboratory


a methodology presented at a 2004 SME conference on advanced energy and fuel cell technologies. Energy usage in manufacturing facilities encompasses direct production of goods, space conditioning and general facility support, such as lighting. With as few as 60 easily obtainable data points, the lean analysis method graphically and statistically develops multivariable change-point models of electricity and natural gas use as functions of outdoor air temperature and production data. A paper from MSEC 2014 (paper #4014) by Clemson Uni-


versity (Greenville, SC) and BMW Manufacturing Co. (Greer, SC) authors focuses on a multiobjective optimization strategy for a plant-level energy supply system. With an example from an automotive assembly manufacturer, a complex multiple- input, multiple-output (MIMO) system was used for single- objective optimizations and linearly scaled multiobjective optimization to analyze energy, economy and environment in the representative plant. Three aspects were identifi ed for future work: better forecasting of energy demand and opera- tions strategies; development of shorter time resolution, such as minute and second modeling of equipment operational dy- namics; and consideration by economic analysis of the equip- ment, construction and labor cost of energy management.


The Molecular Foundry at the Lawrence Berkeley National Lab (Berkeley, CA) is exploring dynamic nanointerfaces for novel functionality in environments that are out of equilibrium, such as in solar cells.


Two papers from 2003’s International Conference on Composite Materials (ICCM-14; San Diego) describe the use of fi bers in battery composition. The fi rst paper (http:// tinyurl.com/tp04pub113) covers development of solid-state, thin-fi lm rechargeable batteries on fi ber substrates for energy and power storage in novel, stand-alone thin-fi lm battery applications, power composites and electrotextiles. In the second paper (http://tinyurl.com/tp04pub68), dual-function carbon fabric composite anodes are analyzed for strength and electrochemical activity.


Plant-Level Energy Analysis Lean energy analysis (http://tinyurl.com/tp04pub337) is


Energy-Conscious Scheduling Reducing energy cost in a factory may seem as simple as running machines at off-hours or turning down the heat and lights, but energy-conscious scheduling of a manufactur- ing facility is more complex and less fl exible than is energy consumption management in residential and commercial buildings. Purdue University’s Hao Zhang, Fu Zhao and John Suther-


land proposed the feasibility of reducing electricity cost for a manufacturing factory through scheduling in a smart grid scenario while maintaining production throughput. A hypo- thetical region including a power distribution/transmission system, residential/commercial buildings and a fl ow shop operating 8/16 working hours/day was considered (MSEC 2014-#3926).


In an accepted NAMRC 2015 paper (#64), the same


Purdue researchers expand on the theme by applying it to multiple collaborative factories to reduce energy cost. The multiple-factory scheduling problem is decomposed into suboptimization formulations by assigning each factory a virtual electricity price that is determined by the hourly power consumption threshold, the factory’s energy consumption and the predicted demand from all factories. Additional rules might need to be applied to proportionally reallocate electric-


26 — Energy Manufacturing 2015


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