KPI intelligence for energy management in manufacturing

Nowadays, companies have to consider efficient use of energy and resources in manufacturing besides traditional performances to become and remain competitive in their respective industry. Thus, manufacturing firms must put more efforts on in-depth analysis of energy and resource performance within their manufacturing processes and facilities. A comprehensive process design and plant optimization with a specific focus on energy efficiency is of paramount importance for this purpose. Currently, such appropriate concepts and tools for dealing with energy efficiency as a performance criterion are too few in the manufacturing industry and the existing ones mainly lack holistic consideration of the overall plant. Potentials to improve energy efficiency are far from being exploited as mentioned by many scholars. This study is based on the main problem that there is a lack of holistic methodology and decision support for handling the energy efficiency issue in manufacturing. Hence, this research intends to establish a basis for the companies and academia to have an understanding on how to successfully integrate energy efficiency in manufacturing and to understand the role of ICT as an enabler for energy efficient manufacturing, investigating how ICT can be facilitated accordingly. To this end, primary focus of this study is the lack of KPI Intelligence in manufacturing with respect to energy efficiency. This scope has been identified by the preliminary research including critical review of the literature on energy efficient manufacturing and an industrial survey complemented by interviews, carried out to highlight the gaps between theory and practice, as well as the importance of different aspects in integrating energy efficiency in manufacturing. Hence, this dissertation aims at bringing energy related KPI Intelligence in manufacturing by developing models to create appropriate KPIs and increasing the visibility and transparency of these KPIs, facilitating ICT as an enabling factor. Accordingly, the research is divided into two parts: The first part aims at developing a novel methodology for the design and use of energy related KPIs to support decision making in energy management. The proposed cross view methodology generates Energy KPIs according to cause- effects relationships between manufacturing system and energy consumption, and allows to effectively exploit the potential brought by energy measurement and monitoring technology in order to provide energy manager detailed information to properly address continuous improvement of energy performances. The second part supports the first part by developing an approach to improve energy efficiency in manufacturing by facilitating monitoring and control through ICT-supported KPI intelligence serving as a decision support tool to enhance energy management in manufacturing plants. The aim is to foster consistent and continuous calculation of KPIs for which the variables come from disparate data sources and hence increase the visibility and transparency of the identified KPIs. The principal beneficiaries of this study are energy managers and plant managers of manufacturing companies, who have the goal of improving energy efficiency in their manufacturing system through strategic approach. Since the dissertation will also highlight the gap between academia and industry serving as a reality check between what is being developed in theory and what is implemented in the real business context and thus help to identify future research directions in the area, academics in energy related research fields will benefit from the findings as well.