Calculation of Energy Footprint of Manufacturing Assets
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Energy efficiency is one of the important topics in manufacturing sector, primarily due to increasing energy prices, ecological concerns and stringent regulations. Industries that have already spent many years in improving energy efficiency now find it difficult to propose and implement additional improvement measures. This thesis proposes a way to identify potential areas for improvements in energy efficiency by calculating energy footprint of the manufacturing assets. The information on energy footprint is provided using analytic tools. The main goal of the thesis is to demonstrate how energy footprint can help in making decisions regarding the manufacturing facility that may lead to improvement in the overall energy efficiency of the system. For purpose of energy data analysis, a methodology is proposed in which the analytic tools are developed as web services. This methodology is suitable for implementation within a service-oriented manufacturing facility. The core analysis of data is carried out using MATLAB due to its powerful data analysis capabilities, high level programming, availability of relevant libraries, easiness in data handling and manipulation. MATLAB functionalities are deployed in Java and are published as web services. The classes in Java are mainly responsible for message parsing and sending/receiving data from MATLAB functions deployed in Java. The work demonstrates the usefulness of analytic tools in analyzing energy footprint of manufacturing assets. The work also demonstrates applicability of service-oriented approach for data analysis and availability of analytic tools as web services in a service-oriented manufacturing system. The service-oriented approach enables extensibility of analytic web services and online availability. This study results in development of analytic tools helpful in analysis of energy footprint of manufacturing assets within a service oriented manufacturing system. Energy footprint helps in identifying potential areas for improving energy efficiency.