Context sensitive production planning and energy management approach in energy intensive industries

• The context sensitive approach for energy management is presented.
• The framework for performance monitoring and targeting is introduced.
• The approach for on-line CO2 emissions monitoring and targeting is presented.
• Key implementation challenges in cement plants are discussed.

The need for competitiveness on the global market is the main driver for industrial companies to systematically and continuously analyse all possibilities for the optimisation of production process and related costs reduction. Modern industrial processes are increasingly complex with highly dynamic energy use patterns. A systematic approach to industrial energy system analysis requires proper understanding of interactions among the main factors influencing energy performance. Also, systematic approach takes into consideration not only efficiency of individual equipment or machines but also their performances within a system where each piece of equipment delivers specific function.This paper presents a context sensitive production planning and energy management approach for achieving energy savings and emissions reduction in energy intensive industry. Combination of decision support for production planning and simulation of possible future situations with context sensitive monitoring and targeting are vital elements of proposed approach and are necessary for continuous improvement of energy performance. The proposed approach includes four building blocks: (1) ambient intelligent data acquisition and context processing, (2) energy modelling and emissions calculation including the prediction engine, (3) decision support services and the (4) knowledge repository. The proposed approach has been tested in the real industrial environment and initial testing results are indicating the potential of the proposed approach to initiate sustainable changes in the production process. Also, external factors that are beyond control but which do influence daily operations of energy intensive industrial companies have been analysed, for example process operators' behaviour and variations in production outputs.