Implementing energy management into operations: devolopment of a multi-variable framework for real-time controlling of energy consumption within manufacturing systems

The area of energy management in the application domain of industrial sector is relatively new and encompasses several different disciplines. In consideration of a major focus on sustainability and increasing costs, primarily, the challenge in industrial plants lies in the reduction of energy consumption by establishing methods to interface between energy expenditure and load requirements of production. This dissertation is an attempt to provide a new perspective to the problem description of integrating operation and energy management best practices through the monitoring and control of energy consumption. Its final aim is to contributing to the continuous improvement of a manufacturing plant in a more extended way. The overall approach to the problem borrows from the basic principles found in quality management and lean production methodology; the interconnections between wellknown lean concepts and energy consumption under demand constraints is exploited to form a well-defined modular framework, permitting this multidisciplinary problem to be approached systematically. To face the multi-dimensional aspects, the inter-linkages and the complexity of this integration, present framework was structured into two main fronts, respectively levers on quantity and levers on price. In the former, after the characterization of the energy patterns both for utilities and production process, the opportunities derived by an effective energy monitoring and control will be illustrated, taking into account its impact on maintenance strategies, scheduling and identification of virtuous behaviors. In particular, the impact of single Overall Equipment Effectiveness losses on energy consumption will be tested through the analysis of a thermoforming process conducted in a real plant. Conversely, in the latter, the opportunities to lower the unit energy cost on the basis of energy patterns will be exploited through the analysis of both active (i.e. autoproduction) and passive (i.e. load shifting) levers. Finally, a classification of plants considering the energy profile will be provided in order to address future energy audits and create a mechanism of continuous improvement.