New Manufacturing Environments with Micro- and Nanorobotics

UIDB/04647/2020 UIDP/04647/2020The convergence of nano-, bio-, information, and cognitive sciences and technologies (NBIC) is advancing continuously in many societal spheres. This also applies to the manufacturing sector, where technological transformations in robotics push the boundaries of human–machine interaction (HMI). Here, current technological advances in micro- and nanomanufacturing are accompanied by new socio-economic concepts for different sectors of the process industry. Although these developments are still ongoing, the blurring of the boundaries of HMI in processes at the micro- and nano- level can already be observed. According to the authors, these new socio-technical HMIs may lead to the development of new work environments, which can also have an impact on work organization. While there is still little empirical evidence, the following contribution focuses on the question whether the “manufacturing (or working) life” using enhancement practices pushes the boundaries of HMI and how these effects enable new modes of working in manufacturing. Issues of standardization, acceleration of processes, and order-oriented production become essential for technological innovation in this field. However, these trends tend to lead to a “manufacturing life” in work environments rather than to new modes of work in industry.publishersversionepub_ahead_of_prin

Human Aspect on Chain of Custody (CoC) System Performance

The tropical forests cover 24% of tropical land area. They are the most productive terrestrial ecosystems on earth with high priorities for biodiversity conservation. These forests store a substantial amount of carbon in biomass and soil, and they also regulate the transfer of carbon into the atmosphere as carbon dioxide (CO2). Indonesia is having the third tropical forest area in the world after Brazil and Congo. Over 50 years forest has been felled both legally as well as illegally. High rate of forest degradation resulted from unsustainable forest management, rampant illegal logging, forest area encroachment, conversion and natural disaster. All urges rapid improvement of management system of Indonesia’s forest resources (Holmes, 2002). Forest certification is one tool that can support the achievement of sustainable forest management goal. Under current operation of join certification protocol between the Forest Stewardship Council (FSC) and the Indonesian Ecolabelling Institute (LEI) in Indonesia, forest management units must be able to show the required performance indicated in LEI criteria and indicator as well as FSC principles and criteria to attain certification of their products. The gap between current practices and performance required by forest certifications schemes is still enormous. The performance of forest certification system from LEI is determined very much by the human that is involved in the process of planning and operation. The name of certification system is chain of custody (CoC) certification. CoC operation involves activities such as tracing raw material from the forest to the factory, through shipping and manufacturing, to the final end product. In all of the above processes, the roles of human are critical, although the specific roles played from one process to another are different. In this paper we present an identification of human aspect and other factors that predominantly affect CoC system performance

Low-cost Automation – changing the traditional view on automation strategies using collaborative applications

The labor cost has been one of the main reasons for industry to move some of the production to so called low-cost countries. Research has shown that this issue is more complex than just calculate labor cost as main driver. Organization culture, research and development and technical competence is also important drivers for a successful automation strategy. Another important factor when it comes to automation strategies is what production parameters to consider choosing the right automation. Traditionally five parameters have been considered i.e. Volume, batch sizes, variants, investment cost and labor cost. With new and cheaper solutions for automation these two views on automation and lowcost production need to be considered and changed. This paper will describe three demonstrators using low-cost automation solutions to automate simple tasks in final assembly systems. The stations\u27 investment cost is all below 50,000 euro. The first demonstrators have been set up and tested in a lab environment. The results show a high precision, easiness in programming and high quality. The aim is to test this further in real industrial environment to stress the system and to put it into a tougher environment

Supply Chain

Traditionally supply chain management has meant factories, assembly lines, warehouses, transportation vehicles, and time sheets. Modern supply chain management is a highly complex, multidimensional problem set with virtually endless number of variables for optimization. An Internet enabled supply chain may have just-in-time delivery, precise inventory visibility, and up-to-the-minute distribution-tracking capabilities. Technology advances have enabled supply chains to become strategic weapons that can help avoid disasters, lower costs, and make money. From internal enterprise processes to external business transactions with suppliers, transporters, channels and end-users marks the wide range of challenges researchers have to handle. The aim of this book is at revealing and illustrating this diversity in terms of scientific and theoretical fundamentals, prevailing concepts as well as current practical applications

Production Scheduling

Generally speaking, scheduling is the procedure of mapping a set of tasks or jobs (studied objects) to a set of target resources efficiently. More specifically, as a part of a larger planning and scheduling process, production scheduling is essential for the proper functioning of a manufacturing enterprise. This book presents ten chapters divided into five sections. Section 1 discusses rescheduling strategies, policies, and methods for production scheduling. Section 2 presents two chapters about flow shop scheduling. Section 3 describes heuristic and metaheuristic methods for treating the scheduling problem in an efficient manner. In addition, two test cases are presented in Section 4. The first uses simulation, while the second shows a real implementation of a production scheduling system. Finally, Section 5 presents some modeling strategies for building production scheduling systems. This book will be of interest to those working in the decision-making branches of production, in various operational research areas, as well as computational methods design. People from a diverse background ranging from academia and research to those working in industry, can take advantage of this volume

Simulation for Product Driven Systems

Due to globalisation, companies have to become more and more agile in order to face demand fluctuations and growing customisation needs. Indeed, the mass production market moves to a mass customization one, which could be defined as the production of a wide variety of end products at a low unit cost. During last years, many efforts have been done in order to improve operating system reactivity (with the Flexible Manufacturing initiative for example), but the manufacturing decision process did not really change, and then doesn't enable to fully make the most of these new operating system skills. Facing these new trends, a lot of new research works are focusing on identification technologies, like Auto-ID, biometry or vision ones. Radio Frequency Identification technology (RFID) represents a quick and safe way to track products, opening the way of linking informational and physical flows, and providing an accurate, real time vision of the shop floor. These new technologies appear like a catalyst to change the fifty years old way of controlling production through traditional MRP² systems

From Data to Decision Support in Manufacturing

Digitalization is changing society, industry, and how business is done. For new companies that are more or less born digital, there is the opportunity to use and benefit from the capabilities offered by the new digital technologies, of which data-driven decision-making forms a crucial part. The manufacturing industry is facing the Fourth Industrial Revolution, but most manufacturing organizations are lagging behind in their digital transformation. This is due to the technical and organizational challenges they are experiencing. Based on this current state description and existing gap, the vision, aim, and research questions of this thesis are: Vision - future manufacturing organization to be driven by fact-based decision support based on data rather than of relying mainly on intuition and experience.Aim - to show manufacturing organizations the applicability of digital technologies in digitalizing manufacturing system data to support decision-making and how data sharing may be achieved.Research Question 1. How do manufacturing system lifecycle decisions influence the requirements of data collection towards interoperability? Research Question 2. What makes interoperability standardization applicable to sharing data in a manufacturing system’s lifecycle?This research is applied, addressing real-world problems in manufacturing. For this reason, the main objective is to solve the problem at hand, and data collection methods will be selected that can help address it. This can best be explained by taking a pragmatic worldview and using mixed methods approach that combines quantitative and qualitative methods. The research upon which this thesis is based draws on the results of three research projects involving the active participation of manufacturing companies. The data collection methods included experiments, interviews (focus group and semi-structured), technical development, literature review, and so on. The results are divided into three areas: 1) connected factory, 2) standard representation of machine model data, and 3) the digital twin in smart manufacturing. Connected factory addresses the question of how a mobile connectivity solution, 5G, may be used in a factory setting and demonstrates how the connectivity solution should be planned and how new data from a connected machine may support an operator in decision-making. The standard representation of machine model data demonstrates how an international standard may be used more widely to support the sharing and reuse of information. The digital twin in smart manufacturing investigates the reasons why there are so few real-world examples of this. The findings reveal that a manufacturing system’s lifecycle impacts data requirements, including a need for data accuracy in design, speed of data in operation (to allow operators to act upon events), and availability of historical data in maintenance (for finding root causes and planning). The volume of data was identified as important to all lifecycles. The applicability of standards was found to depend on: 1) the technology providers’ willingness to adapt standards, 2) enforcement by OEMs and larger actors further down a supply chain, 3) the development of standards that consider the user, and 4) when standards are required for infrastructure reasons. Based on the results and findings obtained, it may be stated that it is important to determine what actual manufacturing problem should be addressed by digital technology. There is a tendency to view this change from the perspective of what the digital technology might solve (a technology push), rather than setting aside the solution and focusing on what problem should be solved (a technology pull). This work also reveals the importance of the collaboration between industry and academia making progress in the digital transformation of manufacturing. Proofs-of-concept and demonstrators of how digital technologies might be used are also important tools in helping industry in how they can address a digital transformation