A B S T R A C T This paper aims to provide a systematic overview of the state of the art in energy and resource efficiency increasing methods and techniques in the domain of discrete part manufacturing, with attention for the effectiveness of the available options. For this purpose a structured approach, distinguishing different system scale levels, is applied: starting from a unit process focus, respectively the multi-machine, factory, multi-facility and supply chain levels are covered. Determined by the research contributions reported in literature, the de facto focus of the paper is mainly on energy related aspects of manufacturing. Significant opportunities for systematic efficiency improving measures are identified and summarized in this area. 2012 CIRP.

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Towards Energy and Resource Efficient Manufacturing: A Processes and Systems Approach

Energy-efficient scheduling in manufacturing companies: A review and research framework

Energy consumption model and energy efficiency of machine tools: a comprehensive literature review

Optimizing the energy efficiency of processes has become a priority in the manufacturing sector; driven by soaring energy costs and the environmental impact caused by high energy consumption levels. The energy consumed by a machine tool performing a turning process consists of not only the energy required by the tool tip for material removal but also the energy used for auxiliary functions. Traditionally, the energy required for the cutting process is estimated based on cutting force prediction equations. However, this estimation is limited to the energy consumption of the tool tip. Thus, the aim of this paper is to develop a reliable method to predict the total energy consumption of a selected machine tool performing a turning operation. In order to compare the energy consumption under different cutting conditions, the specific energy consumption is defined as a functional unit: the energy consumed to remove 1 cm3 of material. An empirical model is obtained based on power measurements under various cutti...

https://journals.sagepub.com/doi/pdf/10.1177/2041297511398541

An empirical model for predicting energy consumption of manufacturing processes: a case of turning process:

Multi-objective optimization of milling parameters – the trade-offs between energy, production rate and cutting quality

Today, energy efficiency in production systems has partially been achieved on the component level, but methods are missing for the energy optimal operation of plants, machines and components. We therefore, propose a novel generic method to model the energy consumption behaviour of machines and plants based on a statistical discrete event formulation. It is lean, integrative and scalable and can be used directly in planning processes to make predictions of the energy consumption of different configurations in different scenarios based on any amount of available information. Using the modelling framework, we introduce applications in real-time, tactical and strategic decision making processes that make it possible to exploit the potential for energy consumption minimisation of any given machine or production system while obeying conflicting general conditions.

A generic energy consumption model for decision making and energy efficiency optimisation in manufacturing

In order to facilitate the process of replacing existing energy sources with sustainable alternatives and to minimize the environmental impact, the energy efficiency not only in consumer and building technology, but also in manufacturing has to be improved. At present, no suitable techniques are available to model and optimize the energy consumption behavior of production machines that take into account how the machines are used. To overcome this limitation, we introduce a lean, scalable modeling formalism that allows making predictions about the energy efficiency depending on design and operation. We present examples for modeling and optimization of a milling machine.

Energy consumption modeling and optimization for production machines

Guaranteeing energy efficient operation of production systems through a-priori optimization is an extremely complex task. We therefore propose an alternative approach where controls can decide locally if an energy reduction is possible and set components to energy-optimal states. In this paper we present results from the research group ECOMATION describing the information flow that generates energy control loops on different levels based on model information and an appropriate communication and control infrastructure. The communication mechanisms and control structures in production systems and machines are presented which allow using models automatically and coherently on all required levels of detail and abstraction.

Architecture for Multilevel Monitoring and Control of Energy Consumption

A prerequisite to achieve energy efficiency in production through optimization is the possibility to use simulation models to predict the consequences settings, decisions and actions have on the energy consumption and thus on the lifecycle cost of production machines. But today’s production systems are dominated by agile structures and rapid changes of general conditions so that predictive energy consumption models need to be adaptable. Therefore in the ECOMATION project the modular modeling approach for energy consumption prediction presented here is being developed, which facilitates re-use of energy consumption models and thus minimizes the cost of finding the optimal operational profiles.

Modular Modeling of Energy Consumption for Monitoring and Control

Resource and energy efficiency have recently come to the attention of production engineers. For optimisation, the energy consumption of various production machines needs to be predicted and integrated into models of complex manufacturing systems. These models and model-based energy consumption optimisation strategies are introduced taking into account time, quality and cost and provide for an absolute reduction of the amount of energy consumed. To maximise operational flexibility while optimising energy consumption the focus lies on methods that optimise the controllable machine and plant parameters in a situation-oriented manner. The paper is concluded with guidelines to apply the techniques in industry. [Received 7 March 2010; Revised 10 July 2010; Accepted 14 November 2010]

Anton Dietmair

Papers

A generic energy consumption model for decision making and energy efficiency optimisation in manufacturing

Energy consumption modeling and optimization for production machines

Architecture for Multilevel Monitoring and Control of Energy Consumption

Modular Modeling of Energy Consumption for Monitoring and Control

Model-based energy consumption optimisation in manufacturing system and machine control