Applied Mechanics and Materials Vol. 805

Abstract: This paper presents a calculation system for evaluating the energy efficiency at machine, plant, location, company, and sector level based on the process specific minimum energy demand. The goal is a comparability of the energy efficiency across machines, plants, locations, companies, and sectors through definition of significant key figures. The basis of the derivation of possible saving potentials is the relative energy efficiency (REE). [7] It is determined by the quotient of minimal energy demand and actually measured consumption and requires that the actually measured energy consumption refers to an independent basis of comparison. The step-by-step development of the calculation system, structured in levels, is based on the detailed analysis of all the influential factors of the energy consumption with the help of cause and effect diagrams to calculate the minimally necessary energy demands for the manufacturing process. Furthermore, the described bottom-up approach delivers, ensuing from the process oriented level of perspective, the step-by-step conception of the calculation method. The REE of a level of perspective is calculated on the basis of the REE value of the previous production level as well as according weighting factors. On the basis of the calculation, as well as subsequent measurements within the company, optimization potentials [10] can be clearly described and can lead back to their roots. These optimization potentials are based on exemplary trials presented for a chosen manufacturing chain of the electronics production area.

Abstract: This paper presents a calculation system to evaluate the energy efficiency in the production in general and at the process level more specifically. Its focus lies on the evaluation of the efficiency of the use of electric energy in the manufacturing industry. The basic target is a comparability of the energy efficiency across products through derivation of significant key figures. The basis of a significant evaluation and overarching comparability of the energy efficiency as well as the basis of the derivation of possible saving potentials is the relative energy efficiency (REE). It is determined by the quotient of minimal energy demand and actually measured consumption and requires that the actually measured energy consumption refers to an independent basis of comparison. The step-by-step development of the calculation system is based on the detailed analysis of all influential factors of the energy consumption. The, in this context, developed Least Energy Demand Method enables the determination of energy minima with different bases of comparison as reference values to evaluate the energy efficiency of single parts production.

Abstract: This paper presents a calculation system for evaluating the energy efficiency of a product regarding its production. In order to evaluate the energy efficiency of the manufacturing of a product value-adding processes as well as auxiliary processes are taken into account. Furthermore, the energy consumption of the periphery, in total is included. Since the total value-added chain of a product usually is not located at only one company, the energy efficiency of the manufacturing of the bought-in parts must also be included. In a last step, the plant specific energy efficiency at the product level based on all plants that produce the observed product can be determined. The basic target is a comparability of the energy efficiency across products by derivation of significant KPI’s. The basis to derive possible saving potentials is he relative energy efficiency (REE), which is the quotient of the minimal energy demand and actually measured consumption. For this, it is required that the actually measured energy consumption is based on an independent basis of comparison. This is assured by the stepped least energy demand method, for a product, based on the process-related perspective level of the bottom-up approach.

Abstract: In electric energy systems based on renewable generation plants supply and demand often do not occur in the same period of time. Consequently demand side management is gaining importance whereby decentralized automation offers opportunities in industrial environments. Compressed air systems on industrial plants consist of air compressors, compressed air reservoirs and compressed air lines. With suitable dimensioning those industrial compressed-air systems can be used for demand side management purpose. As power consumption of industrial air compressors ranges between a few and several hundred kilowatts each, swarms of communicatively connected air compressors can contribute to the stabilization of power grids. To avoid costly production downtime it is to ensure, that a reliable, non-disruptive supply of compressed air can be maintained at all time. Industrial compressed air systems equipped with automation technology and artificial intelligence, which hereinafter are referred to as Cyber-Physical Compressed Air Systems (CPCAS), allow new business models for utilities, industrial enterprises, compressor manufacturers and service providers. In addition to basic operating parameters like current air pressure and status, those systems can process further information and create, for example, profiles on compressed air consumption over time. By enriching those profiles with data on pressure, volumes, system restrictions and current production requirements (plans), the CPCAS can identify the available potential for demand side management. Ipso facto predictive power on electricity consumption is increasing. By providing the information obtained to the power company or a service provider, savings in electricity costs may be achieved. Expenses within the industrial company may be lowered further as compliance with agreed load limits is being improved by automatic shutdown of air compressors upon reaching the load limit. Within this article the structure of the aforementioned Cyber-Physical Compressed Air Systems is presented in more detail, relations between the major actors are being shown and possible business models are being introduced.

Abstract: Establishing energy management in manufacturing major challenge means to increase the energy efficiency of machinery in existing and future processes leading to both, a reduction of energy costs as well as to a reduction of the manufacturing-process-related environmental impacts. Therefore we developed a procedure to prioritize existing machinery for detailed machine examination in order to create a sustainable approach for machine operating companies to prioritise its assets for energy optimisation projects. By using fuzzy logic as method of artificial intelligence nominal and utilisation machinery data as well as inhouse expert knowledge is considered to enhance multi criteria decision making both. Applying this methodology in a series of industrial case studies in discrete manufacturing costs savings of up to 40 percent were realised.

Abstract: Due to increasing cost pressure and competition on the market resource and energy efficient production is inevitable. Energy efficiency projects address this issue through identifying and unleashing energy saving potentials. Green Factory BAVARIA as an institute-spanning research cooperation generates numerous innovative solutions for energy efficiency enhancement in the manufacturing industry through its research projects. Furthermore a great range of energy efficiency measures yet exist. However, when introducing or developing measures for energy efficiency optimization, there is a lack of systematic knowledge and project management, especially in academic research projects. Systematic project management has been established in industry for several years. There are numerous successful examples given in product development as well as in event preparation or reorganization projects. Thus the implementation of systematic project management in universities is essential, precisely because there often is a close cooperation with the industry in particular in the technical and scientific fields. The more widespread the cross-links between the universities are and the more cooperation partners are involved, the more urgent project management tools are required. In this paper we introduce Green Energy Management Portal, a communication and collaboration platform providing both methods and workflows for conducting research projects on energy efficiency as well as a knowledge base for energy efficiency measures. Therefore Green Factory BAVARIA is able to meet its aspiration for transferring knowledge about energy efficiency into industry and thus contributes to a greener Bavarian economy.

Abstract: The paper presents a method to increase the energy flexibility of production systems, establishing a tool to increase the energy flexibility by using the scenario technique. First of all barriers and possible modifications to influence the energy consumption have to be identified. Afterwards, measures can be designed order to address these obstacles. Impacts of the energy conduct on the material flow and production performance indicators will be investigated. These results are necessary for investment decisions for future production plants.

Abstract: Energy efficiency of production systems and of the product itself has grown to a critical competitive factor. Besides the manufacturer’s monetary motivation there are increasing incentives to meet customers’ expectations regarding lifecycle cost and the ecological footprint of products. That neo-ecology, as one megatrend, leads to a new business moral resulting in an energy optimization of the whole product life cycle in terms of resource and energy input. There is a plenty of measures to reduce the energy consumption of a production system and thus to increase its efficiency. To do so companies do not have to develop proprietary solutions for their production sites but can draw on a large pool of measures. However, in practice, many energy optimization measures are unknown to their energy managers. This is mainly owing to the fact that there is no standardized categorization for energy optimization potentials yet. In addition, many efficiency deficits remain undetected as a result of a non-existing efficient methodology for finding energy consumption optimization measures. The domain of information retrieval addresses this issue, as it is able to provide documents matching the user’s information demand. Nevertheless, search queries have to be sufficiently well known in order to gain adequate results. In this paper we show how ontologies can be used to support the user in defining search queries and finding optimization measures efficiently. As formal and explicit specifications of shared conceptualizations, ontologies offer the possibility to represent relevant parts of knowledge in a standardized, machine-readable manner. Therefore, ontologies improve upon data models, which are mainly used for single applications. For the purpose of energy efficiency in production environments, we provide both a methodology to build ontologies for describing energy saving measures and illustrate the application for explicit energy efficiency optimization measures.

Abstract: The term energy management from the past few years is becoming increasingly important. Not only the trend toward clean energy sources triggered a process of rethinking in the minds of society but also pushed the politics to create incentives for companies in order to make them reduce their carbon footprint. The efficient use of energy can be described as an integral part of current political, social and economic decision making.From a business perspective energy efficient production is no longer just considered under the ecological aspect. Through high taxes, huge energy costs and steadily increasing energy prices, there is for companies in the relatively young field of energy management enormous potential to financially improve and consequently save costs sustainably. Furthermore starting from 2015 the energy peak equalization law is made stricter, requiring companies to pay even more in taxes if they fail to fulfill all the requirements set by the politics.Hence the role of energy management systems (EnMS), which deal with the continuous and systematic improvement of the energy performance of businesses, is becoming increasingly important.This paper will deal with an energy management system that was developed by the Institute for factory automation and production systems at Friedrich-Alexander-University Erlangen-Nürnberg. The paper audits the proposed concept and checks it for consistency with the international energy management norm ISO 50001. Additionally all the corrections and necessary optimizations are made in order to provide the companies with a complete energy management system.The aim of this paper is to verify and check the EnMS concept which was developed in the institute for factory automation and production systems (FAPS) for its conformity with the International ISO 50001 standard. Thus ensuring the long term certification according to DIN ISO 50001.