Showing papers on "Production engineering published in 2020"

Assessment of interoperability in cloud manufacturing

Abstract: Cloud manufacturing is defined as a resource sharing paradigm that provides on-demand access to a pool of manufacturing resources and capabilities aimed at utilising geographically dispersed manufacturing resources in a service-oriented manner. These services are deployed via the Industrial Internet of Things (IIoT) and its underlying IT infrastructure, architecture models, as well as data and information exchange protocols and standards. In this context, interoperability has been identified to be a key enabler for implementing such vertically or horizontally integrated cyber-physical systems for production engineering. Adopting an interoperability framework for cloud manufacturing systems enables an efficient deployment of manufacturing resources and capabilities across the production engineering life-cycle. In this paper, the authors investigate interoperability in the context of cloud manufacturing to identify the key parameters that determine whether or not a change-over from traditional cloud manufacturing to interoperable cloud manufacturing is financially viable for a given scenario of service providers and manufacturing orders. The results obtained confirm that interoperable cloud manufacturing systems cannot be considered a one-size-fits-all option. Rather, its applicability depends on a number of driving parameters that need to be analysed and interpreted to determine whether or not it provides a financially viable alternative to cloud manufacturing without an overarching interoperability framework.

Novel methodology for the measurement and identification for quasi-static stiffness of five-axis machine tools

Abstract: Stiffness is an important characteristic of production machinery, as it contributes to its ability to precisely maintain the pose between a tool center point with respect to a workpiece under load. ...

EMG Characterization and Processing in Production Engineering.

Abstract: Electromyography (EMG) signals are biomedical signals that measure electrical currents generated during muscle contraction. These signals are strongly influenced by physiological and anatomical characteristics of the muscles and represent the neuromuscular activities of the human body. The evolution of EMG analysis and acquisition techniques makes this technology more reliable for production engineering applications, overcoming some of its inherent issues. Taking as an example, the fatigue monitoring of workers as well as enriched human–machine interaction (HMI) systems used in collaborative tasks are now possible with this technology. The main objective of this research is to evaluate the current implementation of EMG technology within production engineering, its weaknesses, opportunities, and synergies with other technologies, with the aim of developing more natural and efficient HMI systems that could improve the safety and productivity within production environments.

Integrated computational product and production engineering for multi-material lightweight structures

Abstract: Within product development processes, computational models are used with increasing frequency. However, the use of those methods is often restricted to the area of focus, where product design, manufacturing process, and process chain simulations are regarded independently. In the use case of multi-material lightweight structures, the desired products have to meet several requirements regarding structural performance, weight, costs, and environment. Hence, manufacturing-related effects on the product as well as on costs and environment have to be considered in very early phases of the product development process in order to provide a computational concept that supports concurrent engineering. In this contribution, we present an integrated computational concept that includes product engineering and production engineering. In a multi-scale framework, it combines detailed finite element analyses of products and their related production process with process chain and factory simulations. Including surrogate models based on machine learning, a fast evaluation of production impacts and requirements can be realized. The proposed integrated computational product and production engineering concept is demonstrated in a use case study on the manufacturing of a multi-material structure. Within this study, a sheet metal forming process in combination with an injection molding process of short fiber reinforced plastics is investigated. Different sets of process parameters are evaluated virtually in terms of resulting structural properties, cycle times, and environmental impacts.

Production Engineering Competencies in the Industry 4.0 context: Perspectives on the Brazilian labor market

Abstract: Paper aims With its focus on Production Engineering, the advent of Industry 4.0 is increasingly changing the way things are done. In order to further the knowledge regarding this context as well as understand to what extent Brazil is prepared for digital transformation, this study has a twofold aim: 1) to provide a comprehensive conceptualization on competencies currently required for production engineers working in Brazilian manufacturing industries and, 2) to verify if these competencies are aligned with those established by the Brazilian Ministry of Education for engineering schools. Originality Competencies and skills currently required for production engineers have not been described and researched on a comparable in-depth level before. Research method Initially, a content analysis was conducted in order to compile the main competencies in Production Engineer job listings. Next, a chi-square analysis was performed to assess relationships between compiled competencies. Main Findings The results show that companies are increasingly requiring soft competencies beyond technical expertise, in particular, communication skills. Implications for theory and practice Academicians, educators, as well as policy makers and industry leaders can benefit from the information provided in this study.

Virtual and augmented reality application in production engineering teaching-learning processes

Abstract: Paper aims Structure virtual and augmented reality applications in engineering teaching-learning processes, with emphasis on production engineering, highlighting application gaps. Originality First studies that, to which subjects applied virtual and augmented reality in engineering teaching-learning processes, the gaps of application in production engineering, and a discussion about the impacts. Research method The research method applied was the systematic literature review. Main findings Structuring of virtual or augmented reality applications in engineering, discussion about the application in production engineering, opportunities for future research, how low application affects graduated professional education, consequently, organizational competitiveness. Implications for theory and practice The applications of virtual and augmented reality bring developing student skills more actively and cognitively, making training more complete, increasing their skills, and supporting the competitiveness of organizations through professionals who can contribute more broadly and effectively.

Model Proposal for Diagnosis and Integration of Industry 4.0 Concepts in Production Engineering Courses

Abstract: In Industry 4.0, people need to be able to handle the vast amount of information from machines. In this sense, for Industry 4.0, higher education institutions play a fundamental role. The methodology of this article sought to identify the knowledge required by Industry 4.0 in the literature; carry out a diagnosis of the courses currently offered by Brazilian universities and the need to incorporate new knowledge, and validate the model in a real application. The survey is classified as exploratory, bibliographic and qualitative, supported by bibliometric research. As a result of the research, we identified that the technical content of courses needs to be reviewed to meet Industry 4.0 demand. Sixty-three per cent of respondents were production engineering course coordinators; 70% of respondents considered that the disciplines of current production engineering courses were not adequate to enable the production engineer to work in Industry 4.0. The priority knowledge for implementation in the curricula was identified as big data, advanced simulation, statistics for large amounts of information and virtual reality. It was also considered necessary to bring the industry closer to the universities. The model developed was applied and validated in a university that was evaluated with the highest score in the National Student Performance Exam (Enade).

Production engineering curriculum in industry 4.0 in a brazilian context

Abstract: Industry 4.0 has been discussed in the scientific community since its inception in 2011. Discussions have focused on characterising what Industry 4.0 is. This industry will increasingly require professionals to perform complex and indirect tasks, such as working together with machines in their daily work. This article aims to analyse the skills and competencies required by Industry 4.0, and to compare them with the scope of production engineering disciplines in six Brazilian universities. As a methodological option, the study is classified as exploratory, bibliographic, and qualitative. It is established that the current syllabus of production engineering courses of Brazilian universities needs to be improved, seeking alignment with the skills and competencies required by Industry 4.0. Although the Industry 4.0 theme is being discussed in the scientific field in Brazilian universities, it is not yet possible to identify any key actions taken to adjust and improve production engineering courses.

Towards a business and production engineering concept for individual beer brewing applying digitalization methodologies

Abstract: Individualization is a common trend in many fields of production across the industries. Also in the food sector, significant changes can be observed. For many products, individual offerings towards the customer are meanwhile either mandatory or at least help to increase the sales and revenue. Somehow, individual product design and production contradicts scaling effects, which are especially important for food production. On the other hand, as digitalization is implemented in a fairly limited way in the food sector, currently great chances can be observed to build a unique selling proposition and consequently gain market share by implementing appropriate measures to enable a digital food factory. This is where the proposed idea comes into the game. The starting point is the idea to produce individually developed beer and ship it to the individual customer. The beer can be designed on a web page based on typical parameters, like beer type, bitterness, colour, or alcohol concentration. In an expert mode, individual beer creations may be thoughtful, allowing the creation of completely individual recipes (for sure, not guaranteeing the customer a perfect drinking experience). In any way, the data from the web page is directly fed to the brewing equipment in the brewing facility. There, using newly to be developed specialized machines, the individually ordered beer will be produced automatically. In this paper we discuss the individual challenges at each point in the production cycles and propose solutions to those.

Fundamentals of Mechanical Engineering

Abstract: This book has been focused to bring the appropriate knowledge ingradients spread in different chapters covering mechanical engineering, engineering materials and its composition, properties, use of cast iron, steel, Iron-Carbon equilibrium diagram, properties of materials (physical, chemical, mechanical etc), measurement methods, manufacturing technologies, machine tools, fluid properties and fluid power, thermodynamics and steam engineering, reciprocating engines. This also briefly covers mathematical concepts and its use as an applications tool, basic knowledge of Computerized Numerical Control (CNC) for requisite analysis, artificial Intelligence and machine learning (AIML), MATLAB etc. It is proposed next, to briefly elaborate the pertinent details with some relevant case studies, emanating from the domain of mechanical sciences. Some innovative mechanical engineering projects/entrepreneurial dynamics and its application, internship in engineering sector, make it more versatile and useful inclusions which have been made.

Challenges for Uncertainty Determination in Dimensional Metrology Put by Industry 4.0 Revolution

Abstract: The paper presents the most important challenges for uncertainty determination in dimensional metrology caused by the recent changes in manufacturing and production engineering related to fourth industrial revolution. Current trends in dimensional metrology are described and gaps in the state of art in measurement uncertainty determination are identified. Some propositions on how to fill this gaps are also given. The main finding of the paper is that simulation methods for uncertainty determination based on usage of numerical models of measurement and/or manufacturing processes seem to be the most promising in uncertainty determination for in-process and in-line/in-situ measurement systems and for modern measuring devices like industrial computed tomography systems.

Application of the Philosophy of Management and Production Engineering in Eastern Asia in Improving the Processes of Urban Transport Operation

Abstract: Abstract The subject matter presented in the article touches the problem of incufficient efficiency of processes and systems in organisation. Achievement of adequate efficiency value is a guarantor of competitive advantage of enterprise. Therefore, it is necessary to constantly work on methods and techniques to improve efficiency, tailored to the needs of various organizations, which also includes service enterprises. Service enterprises include public transport companies. The purpose of the latter is to guarantee that the passenger will be transported from stop A to stop B within a certain time. Failure to achieve this goal incurs certain social costs. Therefore, the article focuses on measures and ways to improve efficiency, developed in Eastern Asian enterprises that have been successful as a result of their use. The first part of the article reviews the literature, including the methods used in this part of the world. The second part, however, concerns the possibility of using the BOST method in improving the efficiency of public transport enterprise processes in Poland.

Virtual Tools to Support Design and Production Engineering: Early detection of stone chips to optimize production processes

Abstract: Due to continuously changing boundary conditions, strengthened legislative restrictions, effects of globalization, and those coupled with costs and time pressure, the world of automotive manufacturers is massively changing. In addition to the required reduction of the development- and manufacturing time of automotive products, the costs for these processes have to be reduced. These time- and cost savings require appropriate measures, such as introducing new methods, systems and products, in design and manufacturing plants. In this aspect the development and application of enhanced virtual products in the area of design, simulation and production engineering within various computer-aided engineering environments play a crucial role. Virtual product development has allowed vehicle manufacturers and automotive suppliers to take a large step forward by optimizing engineering processes. Particularly in the early phases of vehicle development it is possible to obtain virtual test results by means of analysis & simulation in order to minimize the costs for physical prototypes in later phases. A good example are crash tests, in which physical prototypes (e.g, car bodies) are largely replaced by virtual simulation models. In this context, the present paper outlines an approach of an integrated virtual product model that intervenes in the early phases of vehicle development in areas such as bodywork development including styling exterior investigations, supporting optimized processes. In addition, the presented approach supports both accelerated time to market and quality improvement in automotive industry.

Workshop development for New frontier of mechatronics for mobility, energy, and production engineering

Abstract: Mechatronics matches the new trend of convergence research [1] for deep integration across disciplines such as mechanics, electronics, control theory, robotics, and production manufacturing, and is also inspired by its active means of addressing a specific challenge or opportunity for societal needs. The most current applications of mechatronics include e-mobility, connected and autonomous vehicles (CAV), robotics, and unmanned aerial vehicle (UAV). The growing mechatronics industries demand high quality workforces with multidiscipline knowledge and training. In this paper we present the working processes and activities of a current one-year ECR: PEER (EHR Core Research: Production Engineering Education and Research) project funded by NSF organizing two workshops held by two institutes. These workshops are to solicit and synthesize insights from experts in the academic, for-profit, and non-profit sectors to describe the future and education of production in mechatronics. Each workshop is planned to be two days, where the first day will be dedicated to the topics of workforce education and training in mechatronics. The topics in the second day will be slightly different based on the expertise and locations of the two institutes. One will focus on the mechatronics technologies in production engineering for alternative energy and ground mobility, and the other will concentrate on aerospace, alternative energy, and the corresponding applications. Both workshops will also address the current technical development of teaching methods and tools for mechatronics. Social impacts of mechatronics technology, expansion of diversity and participation of underrepresented groups will be discussed in the workshops. We expect to have the results of the workshops to present in the annual ASEE conference in June.

Tailored Data Exchange Process to Support Production Engineering

Abstract: Due to progressive globalization, technological advances, climate targets imposed by governments that must be achieved, combined with ever-increasing cost pressure for companies, manufacturing and supplier participants of the production sector are facing an enormous change. In order to counteract these requirements, both development and production processes must be tailored to the new challenges. In addition to the optimization measures, production companies must also consider technology aspects related to climate targets, as already mentioned. A trend that is gaining ground in the automotive industry, as well as in many other industries (e.g. aviation, aerospace, etc.), is the approach of weight reduction through the introduction of new lightweight materials and material combinations. With regard to the automotive sector, the reduction of the total weight as well as further approaches (e.g. new propulsion technologies) have a large potential to contribute to a reduction of exhaust emissions. These changes in the area of materials and the associated joining technology are driving the automotive industry to a significantly change of the data exchange processes between development environments (e.g. CAD - Computer-Aided Design, CAE - Computer-Aided – Engineering) and production-related environments (CAM - Computer-Aided Manufacturing). This paper deals with the data exchange processes of production-relevant information within automotive development and provides an approach to close the gap in this area. Furthermore, the presented approach of a tailor-made optimized data exchange process for production engineering shows an enormous time and cost reduction, and thus an earlier market entry date of products.

Optimized Data Exchange Process between Design and Production Engineering

Abstract: Growing vehicle variant diversity, legal requirements to reduce fleet CO 2 emissions and innovations in the area of drive train technologies, coupled with the increasing pressure to cut costs, pose new challenges for parties in the automotive sector. An implementation of optimized development and production processes supports the effective handling of these challenges. One important aspect includes engineering efficiency improvement by optimizing the entire automotive bodywork development process and the involved data management. Research activities focus on the data exchange processes between design, simulation and production engineering within various CA x environments. This concerns constantly changing boundary conditions and requirements in the area of automotive body development, including but not limited to the introduction of new materials and material combinations and new types of joining technologies. From the viewpoint of an automotive engineering supplier, additional challenges caused by different customer-related development environments have to be considered. To overcome these challenges, various data exchange strategies between OEMs (Original Equipment Manufacturer), automotive suppliers and the use of different data management tools need to be investigated. In this context, the paper presents an approach of an optimized data exchange process of CAD-based data between different CAD (Computer-Aided Design) and CAM (Computer-Aided Manufacturing) environments that supports the entire body development, including data provision for manufacturing engineering. In addition, an optimization of data exchange processes saves development costs and improves the product quality.

International Journal of Advance Research and Innovation

Abstract: Objectives International Journal of Advance Research and Innovation (IJARI) is a peer reviewed, multi-disciplinary journal. The Journal encourages all experienced and qualified young and senior researchers, professionals, and other stakeholders to share their knowledge and experiences. IJARI invites original manuscripts, review articles and innovative research papers. This platform provides an international forum for researchers to exchange ideas in recent advances on various aspects of theories, analysis, experiments and computational methods in science, technology and management. Areas of Interests It is a multi disciplinary Journal, which includes all areas of Science and Technology. Innovative original research papers on topics covered under following broad areas (but not limited to). Mechanical engineering, energy engineering (renewable and non renewable energy), industrial engineering, production engineering, automotive engineering, marine engineering, automation engineering, applied sciences, architecture and building materials, bio-mechanical technology, chemical and material engineering, bio-medical engineering, fluid mechanics, thermal engineering, environmental and civil engineering, computer science & software, electrical system, instrumentation and electronics engineering, mechatronics, information technology, electronics and communication technology, metallurgical science, economic policies and issues, total quality management, optimization techniques, industrial management, etc.

Solving the Challenges of a Complex Integrated Production System in Camisea Field Using Novel Modeling Techniques

Abstract: Camisea asset is possibly the most important mega gas asset in South America, and constitutes for more than 90% of Peru’s gas production. The asset consists of several fields with varying degrees of subsurface complexities, multiple fluid types ranging from very lean to very rich gas condensate. The combined production is routed to gas processing plant via a network of pipelines. The entire development is in an environmentally sensitive area and adds to the complexity of the surface network design process. For these reasons, performing integrated production systems simulations is essential for designing the surface network with appropriate fidelities for each component of the IPSM. In current work, a complex integrated production system was developed for Block A of the asset. It is a 2-field system with complex fluid behavior. The various fluids blend in the well tubings, as well in the combined surface network. The produced gas is treated in the plant for liquid extraction, and dry gas is routed for sales and re-injection. For all this work, a new multi-fidelity IPSM tool was used in both implicit as well as explicit coupling mode. This was achieved by doing both implicit as well as explicit coupling of the reservoir simulation models with well models and surface network model. As a result of this work, a reliable long-term production forecast of the field could be performed. Additionally, the pipe design and network constraints could be evaluated and compression needs variation with time could be assessed. Lastly, with the use of a fit-for-purpose fidelity level for any IPSM component, more efficient and reliable forecasts could be readily generated. A comparison between implicit and explicit coupling of IPSM components is generally missing from the available literature. This study fills in this gap by providing the option to do the two couplings using a single simulation tool, thus providing a consistent comparison. In addition to the various long-term production forecasts, the benefits and drawbacks of the two coupling approaches has been presented in this paper.