Apostolos Fysikopoulos

An Approach to Increase Energy Efficiency Using Shutdown and Standby Machine Modes

Energy efficiency constitutes a very significant factor that requires its inclusion in the manufacturing decision making attributes developing a strategy to produce more with less. The idle state of a machine tool is an inefficient phase. A strategy to increase the energy efficiency of an already balanced production line, using machine tool stand-by or shut-down modes, during the idle phase, is being introduced. This strategy identifies when the application of such modes is gainful from an energy efficiency point of view, based on the available idle time and the consumption of the machine at these modes.

Energy efficiency of laser based manufacturing processes

This paper describes an analytical approach for estimating the energy efficiency of laser machining processes such as laser drilling and grooving. The results of the analysis are used for developing processing strategies.This paper describes an analytical approach for estimating the energy efficiency of laser machining processes such as laser drilling and grooving. The results of the analysis are used for developing processing strategies.

Energy Efficient Process Planning System – The ENEPLAN Project

The key factor to success, towards a competitive energy consumption reduction, is the effective involvement of SMEs both in the use of more efficient machines and in the Design of an Environment for new products. A specific product can be manufactured in different ways, based on cost optimization rather than on production flexibility and energy efficiency with the involvement of different suppliers. The ENEPLAN project aims at the development of a digital and real, energy-efficient, multi-process, networked, manufacturing system, adapted to the functional specifications of metal formed or machined parts for automotive, aeronautic and domestic appliances. Seventeen partners, coming from seven European countries and the participation of OEMs, SMEs, RTD and technology providers, who work jointly to deliver through ENEPLAN a manufacturing planning decision support tool (meta-CAM tool), for the optimization of the plant operation. This tool will be used from the conceptual phase of the product (final blueprints) to its final dispatch to the customer. This paper will provide a short overview of the ENEPLAN project and its ongoing developments, while the existing results will be presented and discussed and the next steps will be described.

On the Design of a Sustainable Production Line: The MetaCAM Tool

Nowadays, manufacturing enterprises face enormous environmental challenges, due to complex and diverse economic trends, including shorter product life cycles, rapid advances in science and technology, increased diversity in customer demands and globalization of production activities. Consequently, the cost is highly affected by environmentally related factors. Energy efficiency is one of the main factors, which together with waste management, affect manufacturing decisions. The complexity and diversity of the factors that determine energy efficiency require intelligent systems for their optimization at each “manufacturing level”. Manufacturing decisions should be taken as fast as possible and with the highest possible accuracy. Artificial intelligence/machine learning tools have made significant progress during the last decade and are suitable for such applications. The main objective of the current study is that an architecture for the development of a networked, online, decision support tool, be provided towards achieving sustainable value chain management. The main idea behind the proposed design is that stakeholders be assisted in taking decisions towards improving the energy and eco-efficiency of the entire value chain or parts of it. This is suggested within the context of a multi-objective optimization procedure, taking into account other important decision making attributes, such as flexibility, quality and time for the final reduction in the overall cost. This architecture incorporates real time information modules that interact with online monitoring systems, using any available information within the value chain and the existing IT tools. A partial realization of the proposed idea is implemented in the form of a user friendly software tool (the MetaCAM tool). This based, decision support tool aiming to optimize a current production line or to propose alternatives for the manufacturing of a product. The tool performs optimization based on a set of predefined criteria, namely energy, waste, cost and time. For each of these criteria, the end-user selects the desired weight factor in order to drive the optimization procedure accordingly. The tool presents the characteristics of the setup of the proposed optimized line and maintains all used data and calculations in order to be reused when necessary. For the tool’s validation, three real case studies from different industrial sectors have been used. The first case study comes from the domestic appliances sector (refrigerator door panel), the second one from the automotive sector (a two seat bench for light commercial vehicles) and finally, the third case study derives from the aeronautics sector and deals with the production of the loading ramp hinge of a military aircraft.Copyright