Hybrid compliance compensation for path accuracy enhancement in robot machining

Robot machining processes with high material removal rates lack of high path accuracy mainly due to the low stiffness of industrial robots. The low stiffness leads to process forces caused deviations of the tool center point (TCP) from the planned position of more than 1 mm in industrial applications. To enhance the path accuracy a novel hybrid compliance compensation is developed. It combines a force sensor and model based online compensation with forces of an offline simulation to instantly react to predictable high force changes e.g. at a milling cutter exit from the work piece. The method is applied to a KUKA KR 300 robot. A compliance model based on a forward kinematic with virtual joints is implemented on an external controller. Cartesian or axis specific compensation values are calculated and transferred to the robot via a control circuit. A compliance measurement method is developed and a force torque sensor is mounted to the flange of the robot. The system is validated in with Cartesian and axis specific compensation values as well as with and without pilot control

Supporting the Transformation to Climate Neutral Production with Shop Floor Management

The European Green Deal proposes the transformation to climate neutrality by 2050. Especially for manufacturing companies and their production sites, this transformation is a big challenge. Every aspect of the value stream needs to be re-evaluated and adjusted to reach the new target state of climate neutral production. In the last decades, many companies used lean management methods to improve production in the dimensions of time, quality, and cost. However, a growing number of studies show that lean methods can also be used to drive sustainability goals (with the target state being climate neutral production). This paper analyses the suitability of shop floor management, a popular lean method, in the context of climate neutral production. To this end, a literature research has been conducted to summarize the goals of shop floor management and the success factors for the transformation to climate neutral production. Then the results are contrasted and overlaps are analysed to identify possible shop floor management tools to accelerate the transformation to climate neutral production. Finally, the findings are briefly discussed and summarized in a matrix. The paper closes with specific recommendations for further research in this area

Optimizing Investment Planning For District Heating Coupling Of Industrial Energy Systems Using MILP

Industrial energy systems are being transformed to decrease energy costs, reduce emissions, and ensure security of supply. The increasing integration of renewable energies and industrial waste heat leads to complex and interconnected industrial energy systems. At the same time, the decarbonization of the heating sector is still in its infancy and possibilities are discussed to make excess heat from industrial companies available for building supply via district heating networks or to use district heating for thermal energy supply in the industrial sector. In this paper, we present an optimization-based investment planning approach to calculate the optimal dimensioning of a potential heat transfer station connecting industrial sites to district heating systems. The approach is based on a model library that includes typical components of industrial energy systems. Moreover, it integrates different energy demands such as heating, cooling, or electricity of production systems and sites as well as waste heat of production processes depending on predominant temperature levels. The approach manages to include transformation strategies of the industrial energy system by integrating different scenarios using regret optimization, giving decision makers a better overview of the impact of the investment in a heat transfer station on the overall factory planning. The approach is applied to the planning process of an industrial company. In the use case, a positive net present value shows the benefits of an investment in a heat transfer station. Moreover, energy costs and carbon dioxide emissions can be reduced over the planning horizon and through the higher utilization of waste heat as well as the more efficient use of energy systems

An Expert System-Based Approach For Improving Energy Efficiency Of Chamber Cleaning Machines

Increased transparency and domain expertise are often prerequisites for identifying energy savings potentials and improving energy efficiency in manufacturing systems. Small and medium-sized enterprises pursuing a reduction in CO2 emissions are especially faced with challenges from the complexity of process data and limited domain expertise. Against this background, this paper presents an expert system for preliminary energy diagnostics using automated energy analysis of production machines and providing measures for improving energy efficiency. Due to their significant energy consumption and increasing importance along various process chains, the use case is developed for chamber cleaning machines. A knowledge base is combined with artificial intelligence techniques for data processing to reveal efficiency potentials based on machine load profiles. The knowledge base created by experts assigns domain-specific information to the automatically processed input data. Key performance indicators are then utilized for internal and external benchmarking and quantification of energy potential, narrowing down promising energy efficiency measures. The suitability of the proposed approach is demonstrated by applying the expert system to two different chamber cleaning machines

Developing GAIA-X Business Models for Production

The manufacturing industry is in the midst of a digital transformation. As part of the increasing internal and external integration of manufacturing companies, ever more significant volumes of data are being exchanged in order to meet the challenges of a globalized production world. The European initiative Gaia-X aims to establish a federal data infrastructure based on European law to ensure data sovereignty in the resulting digital value creation ecosystems. Under the conditions thus created, it will be possible for manufacturing companies to develop entirely new business models. Within the scope of these business models, the benefit of data sharing in the sense of added value will come into focus. The following paper presents opportunities for the development of disruptive digital business models for manufacturing companies in the context of Gaia-X. The paper focuses on how data sharing can be used to create value. Furthermore, it highlights how the transition from technological use case to monetizable value creation can be made with data-based, digital business models in the context of Gaia-X. Finally, the state of work in business model development in the Gaia-X project EuProGigant is presented for discussion and exemplified by two use cases

Modelling and Control of Aqueous Parts Cleaning Machines for Demand Response

With the aim of enabling better utilization of renewable power and reducing the environmental impact of industrial sites, we propose an approach for implementing electric demand response. Cleaning machines provide significant potential for demand response due to their large water tanks, which can be used for thermal energy storage. Furthermore, many batch cleaning machines allow process interruptions without impacting the cleaning result. We show that utilizing inherent energy storage and process interruptions are practical ways to implement demand response. Hence, we present a mathematical demand response model of an aqueous parts cleaning machine and integrate it in a cyber-physical production system. The mathematical demand response model is used to determine the energy consumption of the machine resulting from the cleaning process and the tank heater. The model is divided into an event-based part describing the individual steps of the cleaning process and a time-based part representing the energy required by the tank heater to satisfy specified tank temperature limits. In addition to the mathematical model, we present the data model required for communication with the physical machine. We validate the mathematical model and the complete cyber-physical production system including a real machine in a field test in the ETA research factory for their demand response capabilities

Design Model For Traceability-Supported Assessment Of Product Carbon Footprint

The established approaches for calculating the Product Carbon Footprint (PCF) based on Life Cycle Assessment (LCA) only allow a cause-related determination of used resources to a limited extent. Even in situations where the direct measurement of resource consumption is recommended, PCF calculation is mainly carried out by means of allocation or estimations in industrial practice. In contrast, the use of traceability data offers promising opportunities for increasing the component specific transparency by linking continuously recorded resource flows and data available in software systems with time stamps and component/order IDs (traceability data). Based on the available component-specific database, companies can identify drivers and hotspots of carbon emissions for individual products and derive targeted measures to reduce these emissions. This paper outlines a concept for a traceability-supported design model to determine the PCF based on the existing framework of LCA. Therefore, a literature review is conducted to identify and analyze existing concepts regarding the determination of PCF as well as requirements for a traceability-supported approach. By conducting an expert survey, these requirements derived from literature are evaluated and prioritized. Finally, the results are used to develop a design model for a traceability supported approach to determine the PCF and to indicate future research needs

Process for Climate Strategy Development in Industrial Companies

Climate neutrality has been gaining more and more attention as a long-term goal for companies among different industries. Since this goal can hardly be achieved in the short term and requires a complex interaction of different measures, it calls for a strategic approach. This article presents a strategy process for manufacturing companies striving for climate neutrality. The strategy process consists of three macro phases: preparation phase, strategy development phase and operational implementation phase, which are iteratively carried out. The macro phases are each divided into different meso phases, which include guiding questions that must be answered by different internal stakeholders and process participants. Moreover, necessary results are described which must be available after each phase to enter the next one. The procedure is based on existing models for the description of strategy processes and approaches from the field of energy and environmental management. It combines them into a strategic approach for deriving climate strategies of industrial companies. The developed strategy process is applied to and evaluated at the ETA factory at the Technical University of Darmstadt

Development of Data-based Business Models to Incentivise Sustainability in Industrial Production

Recent environmental catastrophes highlight the need to curb global climate change. Carbon dioxide (CO2) is responsible for the majority of the anthropogenic greenhouse effect. Politicians and society already exerted pressure for some time on industry and companies as major emitters. Despite continuously decreasing emissions, the savings achieved in the industrial sector fall short of the politically set targets. This is mainly due to the fact, that the combination of economic and ecological interests for companies is not promoted sufficiently. As a result, there is a lack of incentives for production companies to reduce their emissions. By incorporating economic aspects, data-based business models can create such incentives and thus support current and future regulatory measures. This paper presents an approach of developing data-based business models to incentivise sustainability in industrial manufacturing. For this purpose, existing and potential future incentive mechanisms for the reduction of CO2 are first identified and discussed. Subsequently, the business model approach for "CO2 reduction in product creation" from the Gaia-X lighthouse project EuProGiant is presented. Finally, this approach is discussed in consideration of possible emission savings and the compatibility of economical and ecological company interests

Lightweight hybrid CFRP design for machine tools with focus on simple manufacturing

There is a continuing demand in machine tools for an increase in productivity. This can be achieved by higher speeds and process parameters, which demand structures with a high stiffness to weight ratio including the use of materials with a high specific modulus. The lack of standardized interfaces and more complex design and manufacturing process prevent the broad use of these materials. This applies especially for CFRP (carbon fiber reinforced polymer) which has the highest specific modulus compared to conventional construction materials. Due to that and the higher material damping in comparison with steel, parts out of CFRP can improve the precision of machine tools. These advantages often remain unutilized because of the challenging integration of CFRP parts. Therefore, this paper presents an innovative approach to use CFRP in a hybrid design for machine tool structures focusing on improved dynamic behavior, increased specific stiffness, and ease of manufacture