Energy Efficiency in Strategy of Sustainable Production Vol. II

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Authors: Markus Brandmeier, Anton Krinner, Jörg Franke
Abstract: Resource and energy efficiency of production facilities is a crucial competitive factor for industry. Due to increasing cost pressure and competition on the market, identifying and unleashing energy saving potentials as well as avoiding inefficiency is inevitable. However, for investment policy, the increase of energy efficiency is not always given highest priority. In this study we consider industry’s investment behavior for energy efficiency in relation to alternative production factors. For this purpose, this paper analyzes potential optimization issues and criteria that are taken into consideration for the decision making process for investments.
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Authors: Eric Unterberger, Adam Wolf, Gunther Reinhart
Abstract: Industry is one of the major energy consumers in Germany. In order to fulfil the social responsibility of the energy revolution, companies required to install and to use their own renewable energy. With the increasing set-up of renewable energy systems at the production site, these companies are interested in consuming most of the energy directly on-site. Based on a material flow simulation of the Green Factory Bavaria in Augsburg, this paper compares different indicators for the energy self-sufficiency. Finally the effect of electrical energy storage to increase the energy self-sufficiency is examined.
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Authors: Mario Serno, Carmen Renz, Stefan Endrizzi, Peter Schuderer, Jörg Franke
Abstract: This article introduces a method and a software-tool for comparing inbound logistics systems in respect of energy consumption. In the field of green logistics numerous methods are already existing, but mostly they focus either on the evaluation of the energy consumption of single logistics components or the improvement of the energy efficiency of logistics processes. There is no hands-on solution which can be used in the rough planning phase of logistics projects to evaluate and compare whole system configurations. With the new method we try to fill this gap by integrating existing methods to a holistic approach. It comprises three steps: “identification”, “quantification” and “aggregation and comparison”. In the identification step every system variant will be divided into subsystems and components by using a hierarchical representation. Quantification means to determine the energy consumption of every component by using physical models or reference values. In the last step the resulting energy values will be summed up to an overall figure which can be used to compare multiple system variants. The Sofware-Tool E|stimate is for the part automation of the calculation method. It comprises a component for transport logistics, one for intralogistics and one for the analysis of the aggregated consumption. In summary, the new method and software-tool enables practitioners to compare inbound logistics system variants quickly with sufficient precision. Because of its ease of application, it contributes to implement the concept of sustainability in daily business.
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Authors: Sven Kreitlein, Fabian Ultsch, Fabian Baumhoer, Jörg Franke
Abstract: This paper presents the Least Energy Demand as a comprehensive reference value to evaluate energy efficiency. An objective evaluation and calculation of the energy efficiency of production processes represents a substantial challenge with regard to the state of the art. The reason for this is the lack of appropriate reference values. A comprehensive comparison of the energy efficiency is not possible without consistent reference values. However, this comparison is essential to reveal the actual energy savings potential of production processes and to derive actions on its basis. First, in order to calculate such a reference value for different production processes, the basics to describe a closed system energetically, are defined. Initially, several energy states and the various energy terms were defined to describe a production process as an energetic system. In a second step, the model for the activation energy based on chemical laws is introduced and its basic idea is transferred to the operations of the production processes of DIN 8580. For this purpose, appropriate general conditions have to be defined in order to be able to derive, finally, the existence of a Least Energy Demand for the execution of a production process according to DIN 8580. In conclusion, the term Least System Energy Change Demand is introduced and is defined within the conceptualized model for the activation energy. It forms the basis of independent reference values for the evaluation and calculation of the energy efficiency of production processes.
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Authors: Sven Kreitlein, Fabian Baumhoer, Fabian Ultsch, Jörg Franke
Abstract: This paper presents the Least Energy Demand as a comprehensive reference value for evaluating energy efficiency. An objective evaluation and calculation of the energy efficiency of production processes represents a substantial challenge with regard to the state of the art. The reason for this is the lack of appropriate reference values. A comprehensive comparison of the energy efficiency is not possible without consistent reference values. However, this comparison is essential for revealing the actual energy savings potential of production processes and for establishing actions on its basis. Therefore, the first step is to define the general conditions necessary to transfer the model concepts from the microscopic to the macroscopic level for the calculation of the Least Energy Demand. Then, the transferability is verified by reducing the macroscopic material parameters, which determine the amount of the Least Energy Demand significantly, to their atomic interrelations. Moreover, the unit operation-specific Least Energy Demand EGM is introduced on the basis of the unit operation and can be spent through several forms of energy. In conclusion, the importance of the EGM as a reference value for evaluating the energy efficiency of production processes of the DIN 8580 is explained. The EGM of the evaluated production process is the result of the energetic interrelations of the unit operation (s). These are identified and shown for the considered production process according to the DIN 8580.
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Authors: Sven Kreitlein, Fabian Baumhoer, Fabian Ultsch, Jörg Franke
Abstract: This paper presents the Least Energy Demand as a comprehensive reference value to evaluate energy efficiency. An objective evaluation and calculation of the energy efficiency of production processes represents a substantial challenge with regard to the state of the art. The reason for this is the lack of appropriate reference values. A comprehensive comparison of the energy efficiency is not possible without consistent reference values. However, this comparison is essential for revealing the actual energy savings potential of production processes as well as to derive actions on its basis. In order to calculate such a reference value for different production processes, the term Least System Energy Change Demand is defined based on the model of the activation energy in the field of chemistry and on the given circumstances. In the following, the fundamental model concepts for describing the processes on an atomic level, which take place during the execution of the respective production process according to DIN 8580, are introduced. Four fundamental models consider the atomic processes under energetic aspects: 1. the chemical, 2. the atom physical, 3. the thermodynamic, and 4. the materials scientific model. The atom physical model includes two model concepts that describe different phenomena: the model concept of the potential well and the model concept of the Coulomb potential. Finally, it is shown to what extent the models can be transferred to the common materials in the manufacturing technology. The presented models form the basis for determining the Least Energy Demand as a reference value to evaluate and calculate the energy efficiency for production processes according to DIN 8580.
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Authors: Paryanto, Matthias Brossog, Manuel Roppelt, Jörg Franke
Abstract: An energy-efficient handling system can only be constructed on condition that at the beginning of the development process the energy behavior of handling machines can be evaluated. However, the challenge at the beginning of the development is characterized by the fact that there is no energy data of these machines available. Most of the machine manufacturers do not provide such data or they only offer general data, which is limited to special machine conditions or movements. To solve this challenge, a model-based approach for energy monitoring of handling processes is developed. This approach allows the planning engineers to analyze the energy behavior as well as the kinematic behavior of handling machines at their real conditions. The approach is developed using the multi-domain simulation method, so the detailed components of handling machines can be modeled and simulated. Based on the case study analysis that was performed on a Cartesian robot, the developed approach is conveniently used to predict the energy consumption behavior of handling machines. Thus, using the developed approach, a planning engineer can reduce the energy consumption of handling systems by optimizing the handling sequence.
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Authors: Thiemo Müller, Julian Stefan Tauschek, Johannes Glasschröder, Gunther Reinhart
Abstract: An increasing number of companies establish energy management systems for continuous improvement in their energy efficiency and for this intensify monitoring their current energy consumption. These data can be used to gain further information about the production and to find potentials to increase its energy efficiency. In the procurement process of machinery and equipment or in the planning phase of production systems and building services, information about energy demand is rarely available, though it would be valuable for an early inclusion of energy efficiency in these processes. Therefore this paper discusses different forecast methods for energy consumption of machinery and evaluates in particular their universal applicability, effort and accuracy by analyzing them through the example of a packaging machine. In addition this paper proposes a further usage of energy-related data of machinery, which can be automatically acquired by monitoring systems for prognosticating their energy consumption as well as a possible distribution approach of this information. Therefore an own forecast method is presented, which shall process the energy-related data combined with information about dominant parameters of the product, the usage of the machine and the environmental conditions. For the distribution concept it was taken into account that the generated and shared information has to be abstracted in a way that no critical secrets of the company are revealed.
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Authors: Cedric Oette, Thomas Küfner, Arnim Reger, Johannes Boehner
Abstract: Due to the rising energy costs and the increasing competition on the market the improvement of the energy efficiency in production systems can be a great chance for companies to gain an advantage compared to their competitors. Therefore, the transparency of the energy consumption of the several processes of such systems has to be known in detail. In this paper a method for the detection of operating states in production systems, based on big data analysis is introduced. The developed algorithm automatically detects different operating states in the current profile and improves his accuracy the longer it is used. To evaluate the developed data analysis algorithm, a defined process with a conveyor belt was considered and measured several times. The algorithm defines clusters from the measurements and identifies classes for the several operating states. With the naive Bayes classifier it is possible to categorize the clusters more fine-grained and faster than with a correlation function. An advantage of the method is that each new classified instance is taken into account for future unclassified instances. So it is possible to integrate a continuous learning process in production processes and to consider a slowly drift of states. Also, the subsequent addition of classes and attributes that are represented in this work by clusters, is possible at any time.
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