Industrial decarbonization by a new energy baseline methodology. Case study

The main target of climate change policies in the majority of industrialized countries is to reduce energy consumption in their facilities, which would reduce the carbon emissions that are generated. Through this idea, energy management plans are developed, energy reduction targets are established, and energy-efficient technologies are applied to achieve high energy savings, which are environmentally compatible. In order to evaluate the impact of their operations and investments, companies promote measures of performance in their energy management plans. An integral part of measuring energy performance is the establishment of energy baselines applicable to the complete facility that provide a basis for evaluating energy efficiency improvements and incorporating energy performance indicators. The implementation of energy management systems in accordance with the requirements of ISO Standard 50001 is a contribution to the aim and strategies for improving cleaner production in industries. This involves an option for the industry to establish energy benchmarks to evaluate performance, predict energy consumption, and align production with the lowest possible consumption of primary and secondary forms of energy. Ultimately, this goal should lead to the manufacturing of cleaner products that are environmentally friendly, energy efficient, and are in accordance with the global environmental targets of cleaner manufacturing. This paper discusses an alternative for establishing energy baselines for the industrial sector in which several products are produced from a single raw material, and we determined the energy consumption of each product and its impact on the overall efficiency of the industry at the same time. The method is applied to the plastic injection process and the result is an energy baseline (EBL) in accordance with the requirements of ISO 50001, which serves as a reference for determining energy savings. The EBL facilitates a reduction in energy consumption and greenhouse gas emissions in sectors such as plastics, a sector which accounts for 15% of Colombia’s manufacturing GD

Mass Production Processes

It is always hard to set manufacturing systems to produce large quantities of standardized parts. Controlling these mass production lines needs deep knowledge, hard experience, and the required related tools as well. The use of modern methods and techniques to produce a large quantity of products within productive manufacturing processes provides improvements in manufacturing costs and product quality. In order to serve these purposes, this book aims to reflect on the advanced manufacturing systems of different alloys in production with related components and automation technologies. Additionally, it focuses on mass production processes designed according to Industry 4.0 considering different kinds of quality and improvement works in mass production systems for high productive and sustainable manufacturing. This book may be interesting to researchers, industrial employees, or any other partners who work for better quality manufacturing at any stage of the mass production processes

The impacts of Industry 4.0 enabling technologies on operational strategy

Purpose: Adapting to technological advances is a pertinent challenge for operations in the Manaus Industrial Park. This study aims to address the following research question: how do Industry 4.0 (I4.0) enabling technologies impact the quality and flexibility strategy in the Manaus Industrial Park? Originality / Value: This study developed a systematic and structured way to understand the benefits of I4.0 technologies in quality strategies and flexibility of manufacturing production lines. Manaus Industrial Park plays an essential role in the development of innovations in the Amazon region, and companies must be competitive in this new context of digitization of manufacturing. Methods: This study used a qualitative and descriptive approach. Data were collected through semi-structured interviews with industrial managers from 12 companies that operate in the Manaus Industrial Park. Results: The results of this work point to a frequent use of computer systems to integrate machines in operations, such as the use of M2M technology and cyber-physical systems. The companies researched in the Manaus Industrial Park are adopting essential technologies to create the infrastructure for the I4.0 implantation. This is the first step to making smart factories in the future. Conclusions: Industry 4.0 enabling technologies affect operations' quality and flexibility strategy, promoting cost savings by optimizing production processes

Production of plastic injection moulding tools using selective laser sintering and high speed machining

Global manufacturing trend and competition challenge every industry to seek new manufacturing methods to improve their business processes and speed up the product development cycle [Conolly, 2004a and Knights, 2001]. Among the candidates, layer manufacturing (LM) technologies appear to be a potential solution [Plam, 2002, and Grimm, 2004]. Recent LM technologies have led to a demanding application for developing production tools to manufacture parts, known as rapid tooling (RT). Selective laser sintering (SLS) is one of the leading LM systems available today in RT to manufacture injection mould (core/cavity) inserts [Kruth, 1998, Chua, 1999, Dormal, 1999, and Grenda, 2005]. However, the current capabilities of the SLS in producing metal parts have not yet fulfil the requirements of the injection mould inserts, especially in dimensional accuracy and surface finish quality [Francis, 2002 and Dalgamo, 2001 a]. The aim of this research is to use indirect SLS and high speed machining (HSM) in developing production-quality plastic injection moulding (core/cavity) inserts. The idea is that the indirect SLS process is utilised to build a near-net-shape inserts, while HSM is then utilised to finish the inserts to production specifications. Benchmark studies have been carried out to characterise the capabilities of both SLS and HSM with reference to the typical requirements of injection mould inserts. Utilising the study results, new developments of the mould inserts have been implemented on three major industrial case studies. Their performances have been evaluated and measured by comparing them with its respective original inserts. Furthermore, a set of design rules has been derived from best practices of the case studies, and have been validated by developing a new design for each case studies inserts. The results have demonstrated that the indirect SLS process has a capability III manufacturing a near-net shape of the insert which requires further related finishing to achieve final production specifications. The insert performances in some case studies have indicated significant improvements in process productivity and energy consumption as well as economic benefits to using the inserts. Regarding the significant considerations in realising the design, a recommendation on further strategic design rules and manufacturing process are highlighted so that the development of the insert using the selected approach can be more effective and efficient. Moreover, a utilisation of computer analysis software and further durability trial is also highlighted in order to predict and evaluate the optimum overall performance

Environmental impact comparison of distributed and centralized manufacturing scenarios

Centralized manufacturing and distributed manufacturing are two fundamentally different methods for producing components. This work describes a centralized manufacturing scenario in which parts are produced via forging and finish machining at one central location and are then shipped to the end user. The distributed manufacturing model involves a scenario in which an additive manufacturing process (Electron Beam Melting) is used to produce parts to near net shape with minimal finish machining. Because the process doesn\u27t require molds or dies, production can take place in small production quantities on demand at job shops located close to the end user with little transportation. In other words, parts are not produced until they are needed. This is in stark contrast to the centralized model where large quantities of parts are produced and then distributed at a later date when needed from warehouses. The aim of this thesis is to compare the environmental impact of these two different production approaches under a variety of conditions. The SimaPro software package has been used to model both approaches with input from the user involving part size, amount of finish machining, transportation distances, mode of transportation, production quantities, etc. Results from simulation models indicate that at small production quantities, the environmental impact of forging die production dominates the centralized manufacturing model. As production quantity increases, finish machining begins to dominate the environmental impact. Despite the large transportation distances involved, the transportation distance and mode of transportation actually have relatively little impact on overall environmental impact compared with other factors. Regardless of the production scenario being evaluated, the distributed manufacturing approach had less environmental impact. The production of titanium powder as the raw material contributed the majority of environmental impact for this approach. Although this work examines environmental impact, it does not consider the cost of producing a part. It should be pointed out, however, that the distributed manufacturing approach could someday have a profound effect on supply chain management for replacement parts by reducing or eliminating the need for warehouses along with associated inventory carrying costs, product obsolescence costs, heating and cooling energy, etc

Recycling process of permanent magnets by polymer binder using injection molding technique

Seltene Erden-Elemente (REE) werden aufgrund ihrer technologischen Bedeutung und geopolitischen Versorgungskriterien als kritische Metalle eingestuft. Sie werden in einem breiten Spektrum von Anwendungen eingesetzt, einschließlich der Herstellung von Magneten, Batterieelektroden, Katalysatoren und Polierpulver. Viele dieser Anwendungen sind wichtig für die sog. „grünen“ Technologien. Dauermagneten sind hinsichtlich der Marktgröße die wichtigste Anwendung insbesondere für Neodym-, Praseodym-, Dysprosium- und Terbium-Magnete, die in NdFeB-Magneten verwendet werden. Die Nachfrage nach Seltenerdelementen für die Herstellung von Magneten nimmt zu und es wird erwartet, dass sich dieser Trend in den kommenden Jahren fortsetzt. Um die mit der Nachfrage verbundenen Risiken zu verringern, wurden Maßnahmen zur Entwicklung von Recyclingtechnologien zur Wiederverwendung von NdFeB aus Magneten ergriffen. Während der industrielle NdFeB-Schrott bereits zurückgewonnen wird, ist das Recycling von Magneten aus Altprodukten noch weitergehend auf Labor- und Pilotprojekte beschränkt. Diese Abhandlung stellt die Ergebnisse der Materialanalyse vor, die die Möglichkeit bestätigen, magnetische Materialien durch die Einarbeitung in eine Polymermatrix zu recyceln und mittels Spritzgussprozess vorzubereiten. Kern der vorliegenden Dissertation ist die Frage, wie der geschlossene Kreislauf und das Recyclingverfahren von Neodynium Magneten aus Elektroschrott gestattet sein soll. Um diese Frage zu beantworten, sind folgende Aspekte relevant: • Die Wahl der Technologien/Prozesse, die für das Recycling eingesetzt werden. • Nachweis der Wiederverwendung von Neodym-Magneten, die aus WEEE (Waste of Electrical and Electronic Equipment) gewonnen sind. • Herstellung und Analyse von Polymer/Magnet- Compound. • Einfluss der Magnetpartikel, abhängig von ihrer Anzahl und Größe, auf die Viskosität und Fließverhalten des Materials während des Spritzgussprozess. • Analyse des Einflusses der Restmagnetisierung auf das Fließverhalten und einer gezielten Anordnung von magnetischen Partikeln im Bauteil. • Technisch-ökonomische Analyse, die entscheidend dazu beitragen wird, ob und in welchem Ausmaß die Einführung des Prozesses erreichbar ist und damit geschlossene Kreisläufe möglich sind. Auf der Grundlage einer umfangreichen Analyse wurden die optimalen Prozessparameter und die Spritzgussmöglichkeiten des verwendeten Materials vorgestellt. Die Nachfrage nach NdFeB-Magneten in Motoranwendungen wächst und wird in den nächsten Jahren voraussichtlich noch zunehmen. Vor allem die Nachfrage nach E-Bike und E-Autos gewinnt an Bedeutung. Infolgedessen wird die Nachfrage nach schweren Seltenen Erden steigen, was die Entwicklung von Recyclingsystemen für diese Materialien erforderlich macht.Rare earth elements (REE) are classified as critical metals due to their technological importance and geopolitical supply criteria. They are used in a wide range of applications, including the manufacture of magnets, battery electrodes, catalysts, and polishing powders. Many of these applications are important for so-called "green" technologies. Permanent magnets are the most important application in terms of market size, particularly for neodymium, praseodymium, dysprosium, and terbium magnets used in NdFeB magnets. The demand for rare earth elements for the production of magnets is increasing and this trend is expected to continue in the coming years (Langkau S. 2020; Li J. 2020; Goodenough K.M. et al. 2018). To mitigate the risks associated with that demand, have been taken to develop recycling technologies to reuse NdFeB magnets. While industrial scrap is already being recovered, recycling of magnets from end-of-life products is still further limited to laboratory and pilot projects. The following work presents the results of the material analysis, which confirm the possibility to recycle magnetic materials by using a polymer matrix. The main goal of this dissertation is the question of how the closed-loop and recycling process of neodymium magnets from electronic waste should be designed. To answer this question, the following aspects are relevant: • The choice of technologies/processes used for recycling and processing. • Evidence of reuse of neodymium magnets obtained from WEEE (Waste of Electrical and Electronic Equipment). • Process flow analysis and final product evaluation (polymer/magnet compound). • The effect of magnetic particles characteristics (size, distribution, and contribution) on the viscosity and flow behavior of the material during the injection molding process. • Analysis of residual magnetization on the flow behavior and a targeted arrangement of magnetic particles in the component. • Technical-economic analysis, which decisively contributes to whether and to what extent the introduction of the process is achievable. Based on an extensive analysis, the optimal process parameters and the maximum injection possibilities of the material used is discussed along the whole processing line. The demand for NdFeB magnets in motor applications is growing and is expected to increase in the coming years. In particular, the demand for e-bikes and e-vehicles is gaining importance (Kampker A. et al. 2021; Pollák F. 2021; Flores P.J 2021). As a result, the demand for heavy rare earths will increase, necessitating the development of recycling systems for these materials, where this thesis is one basic concept to close the loop

Uses and applications of artificial intelligence in manufacturing

The purpose of the THESIS is to provide engineers and personnels with a overview of the concepts that underline Artificial Intelligence and Expert Systems. Artificial Intelligence is concerned with the developments of theories and techniques required to provide a computational engine with the abilities to perceive, think and act, in an intelligent manner in a complex environment. Expert system is branch of Artificial Intelligence where the methods of reasoning emulate those of human experts. Artificial Intelligence derives it\u27s power from its ability to represent complex forms of knowledge, some of it common sense, heuristic and symbolic, and the ability to apply the knowledge in searching for solutions. The Thesis will review : The components of an intelligent system, The basics of knowledge representation, Search based problem solving methods, Expert system technologies, Uses and applications of AI in various manufacturing areas like Design, Process Planning, Production Management, Energy Management, Quality Assurance, Manufacturing Simulation, Robotics, Machine Vision etc. Prime objectives of the Thesis are to understand the basic concepts underlying Artificial Intelligence and be able to identify where the technology may be applied in the field of Manufacturing Engineering

Dynamic optimisation for energy efficiency of injection moulding process

Low carbon economy has emerged as an important task in China since the energy intensity and carbon intensity reduction targets were clearly prescribed in its recent Twelfth Five-Year Plan during 2011-2015. While the largest enterprises have undertaken initial initiative to reduce their energy consumption, small and medium-sized enterprises (SMEs) will need to share the responsibilities in meeting the nation’s targets. However, there is no established structure for helping SMEs to reduce their efficiency gap and hence the implementation of energy-saving measures in SMEs still remains patchy. Addressing this issue, this thesis seeks to understand the critical barriers faced by SMEs and aims to develop proprietary methodologies that can facilitate manufacturing SMEs to close their efficiency gap. Process parameters optimisation is perceived to be an effective “no-cost” strategy which can be conducted by SMEs to realise energy efficiency improvement. A unique design of experiment (DOE) introduced by Dorian Shainin offers a simplistic framework to study process optimisation, but its application is not widespread and being criticised over its working principles. In order to address the inherent limitations of the Shainin’s method, it was integrated with the multivariate statistical methods and the signal-response system in the empirical study. The nature of the research aim also requires a theoretical approach to evaluate the economic performance of the energy efficiency investment. Hence, a spreadsheet-based decision support system (file SERP.xlsm) was created via dynamic programming (DP) method. The main contributions of this thesis can be subdivided into empirical level and theoretical level. At the empirical level, a technically feasible yet economically viable approach called “multi-response dynamic Shainin DOE” was developed. An empirical study on the injection moulding process was presented to examine the validity of this novel integrated methodology. The emphasis has been on the integration of multivariate techniques and signal-response analysis. The former successfully identified the critical factors to energy consumption and moulded parts’ impact performance regardless of the great fluctuation in the impact response. The latter enables the end-user to achieve different performance output based on the particular intent. At the theoretical level, the “DP-based spreadsheet solution” provides a convenient platform to help the rationally-behaved decision makers evaluate the energy efficiency investments. A simple hypothetical case study on the injection moulding industry was illustrated how the decision-making process for equipment replacement can evolve over time. To sum up, both proprietary methodologies enhance the dynamicity in the optimisation process to support injection moulding industry in closing their efficiency gap. The study at the empirical level was limited by the absence of real industrial case study where it is important to justify the practicality of the proposed methodology. Regarding the theoretical level, the dataset for initial validation on the spreadsheet solution was not available. Finally, it is important to continue the future work on the research limitations in order to increase the cogency of the proprietary methodologies for common use in the industry

New Trends in the Use of Artificial Intelligence for the Industry 4.0

Industry 4.0 is based on the cyber-physical transformation of processes, systems and methods applied in the manufacturing sector, and on its autonomous and decentralized operation. Industry 4.0 reflects that the industrial world is at the beginning of the so-called Fourth Industrial Revolution, characterized by a massive interconnection of assets and the integration of human operators with the manufacturing environment. In this regard, data analytics and, specifically, the artificial intelligence is the vehicular technology towards the next generation of smart factories.Chapters in this book cover a diversity of current and new developments in the use of artificial intelligence on the industrial sector seen from the fourth industrial revolution point of view, namely, cyber-physical applications, artificial intelligence technologies and tools, Industrial Internet of Things and data analytics. This book contains high-quality chapters containing original research results and literature review of exceptional merit. Thus, it is in the aim of the book to contribute to the literature of the topic in this regard and let the readers know current and new trends in the use of artificial intelligence for the Industry 4.0