Preface to the 1st ICI&ME 2018 The ICI&ME is the first International Conference on Industrial and Manufacturing Engineering by the Master and Doctoral Program of Industrial Engineering, University of Sumatera Utara (USU), held from 16-17th October 2018 in Medan, Indonesia, with the theme “Industrial and Manufacturing Engineering Practice for Local Industries”. This conference is an extended collaboration between University of Sumatera Utara (USU), Universiti Teknologi Mara (UiTM), Universiti Sains Malaysia (USM), and Prince of Songkla University (PSU) to intensify knowledge sharing and experiences between higher learning institutions. This ICI&ME Conference is a platform for knowledge exchange and the growth of ideas, particularly in manufacturing engineering. The conference aims to bring researchers, academics, scientists, students, engineers and practitioners from around the world together to present their latest findings, ideas, developments and applications related to manufacturing engineering and other related research areas. With rapid advancements in manufacturing engineering, ICI&ME is an appropriate medium for the associated community to keep pace with the changes. This year, 2018, the conference theme is “Industrial and Manufacturing Engineering Practice for Local Industries” which reflects the role of industrial and manufacturing engineering to be developed for industries. The papers in these proceedings are examples of the work presented at the conference. They represent the tip of the iceberg, as the conference attracted over 167 full papers were accepted in these proceedings. The conference was run in four parallel sessions with 167 presenters sharing their latest finding in the areas of manufacturing process, systems, advanced materials and automation. The Keynote Speaker of this conferences are Prof. Dr. Ir. Abdul Rahman Omar from Universiti Teknologi Mara (UiTM) Malaysia, Rediman Silalahi as Director of PT Perkebunan Nusantara (PTPN IV), Prof. Dr. Ir. Sukaria Sinulingga, M.Eng from University of Sumatera Utara (USU) Indonesia, and Assoc. Prof. Dr. Nikorn Sirivongpaisal from Prince of Songkla University (PSU) Thailand. The organizers are very grateful to them for supporting the conference and sharing their latest research results with the conference participants. As chairman of this International Conference on Industrial and Manufacturing Engineering (ICI&ME), I thank all the committee members that have been involved to make this conference a success and may this conference be blessed by God. Please have a grateful day with ICI&ME. Aulia Ishak, ST, MT, Ph.D. Chairman
Introduction: industrial and manufacturing engineering focuses on designing, improving and optimizing production systems and business operations to improve the efficiency, effectiveness, quality and profitability of companies.Objective: to characterize the scientific production published in Scupus in the Industrial and Manufacturing Engineering research area between 2017 and 2021.Method: observational, descriptive and bibliometric analysis of the articles published in Scopus in the Industrial and Manufacturing Engineering research area between 2017 and 2019. SciVal was used as a metric tool based on the data collected from Scopus for the analysis of the area based on indicators of production citation and collaboration.Result: 357 310 articles were published in the Industrial and Manufacturing Engineering research area, where 21 % responded equally to the Environmental Sciences area, 18,7 to Energy and 17,8 % to the Computer Science area. The most productive themes were the topics T.1114 (n= 3285) and T.3401 (n=1883). 41,1 % of the articles presented only institutional collaboration. According to the percentile based on the CiteScore, 49,2 % of the articles were published in Q1 journals. The Chinese Academy of Sciences was the most productive institution (5 853).Conclusions: scientific production in the Industrial and Manufacturing Engineering area was characterized by increasing trends in volume and decreasing citations, as well as by transdisciplinarity, interdisciplinarity, and international and national collaboration. The articles were mostly published in high-impact journals
This second edition of the classic textbook has been written to provide a completely up-to-date text for students of mechanical, industrial, manufacturing and production engineering, and is an indispensable reference for professional industrial engineers and managers.In his outstanding book, Professor Katsundo Hitomi integrates three key themes into the text:* manufacturing technology* production management * industrial economics Manufacturing technology is concerned with the flow of materials from the acquisition of raw materials, through conversion in the workshop to the shipping of finished goods to the customer. Production management deals with the flow of information, by which the flow of materials is managed efficiently, through planning and control techniques. Industrial economics focuses on the flow of production costs, aiming to minimise these to facilitate competitive pricing.Professor Hitomi argues that the fundamental purpose of manufacturing is to create tangible goods, and it has a tradition dating back to the prehistoric toolmakers. The fundamental importance of manufacturing is that it facilitates basic existence, it creates wealth, and it contributes to human happiness - manufacturing matters. Nowadays we regard manufacturing as operating in these other contexts, beyond the technological. It is in this unique synthesis that Professor Hitomi's study constitutes a new discipline: manufacturing systems engineering - a system that will promote manufacturing excellence.Key Features:* The classic textbook in manufacturing engineering * Fully revised edition providing a modern introduction to manufacturing technology, production managment and industrial economics* Includes review questions and problems for the student reader
This paper is devoted to finding the importance of the factors of industrial and manufacturing engineering for fighting a virus threat and to substantiating the perspectives of increasing quality in the healthcare sphere of based on digitalization and Industry 4.0. The authors perform quantitative analysis of the influence of the factors of industrial and manufacturing engineering on quality of fight against the virus threat in comparison with the traditional factors. A qualitative treatment of the advantages of digitalization and Industry 4.0 with the help of industrial and manufacturing engineering for increasing the quality in fight against the virus threat is provided. The perspectives are modeled and recommendations are developed for increasing the quality of fight against the virus threat based on digitalization and Industry 4.0, with the help of industrial and manufacturing engineering. Originality and advantages of the research consist in the fact that successfulness of fight against the virus threat is treated not from the positions of resources (expenditures) but from the positions of resultsquality. Due to this, the research contributes to formation of a concept of healthcare, which is oriented at the result and which guarantees high quality of medical services. Importance of the research is predetermined by determining the role of the technological factors (industrial and manufacturing engineering) in provision of quality of fighting the virus threat. Significance of the performed research for development of scientific knowledge consists in provision of substantiation and practical recommendations for applying a newdigitalapproach to fight against the virus threat.
The purpose of this paper is to develop a programtarget strategy of quality management in Industry 4.0 and formation of cognitive economy based on industrial and manufacturing engineering in the Russian Federation and countries of the EU. Originality of this research consists in the following. Firstly, the authors specify the essence, distinguish and determine the elements of quality in Industry 4.0, offer estimate indicators and use them to perform a polycriterial evaluation of quality in Industry 4.0, and determine and substantiate the sources of its increase in the Russian Federation and countries of the EU. Secondly, the authors study and prove the strong influence of the factors of industrial and manufacturing engineering on successes in formation of cognitive economy in the Russian Federation and countries of the EU and determine the perspectives of optimizing the influence of these factors of in the interests of formation of cognitive economy. Thirdly, the specifics of causal connections of quality management in Industry 4.0 in countries of Western and Eastern Europe are determined, due to which this research has high empirical value, for its allows developing the specific programs of development of Industry 4.0 in countries of Europe in view of their specific features. Fourthly, the issues of quality management in Industry 4.0 and formation of cognitive economy based on industrial and manufacturing engineering are studied consistently, due to which a general program-target strategy for the Russian Federation and countries of the EU is developed.
Industry 4.0 is the promising area of the industrial revolution and fast-growing network of digitally connected smart devices, equipment/machines and physical objects. It denotes the use of Industrial Internet of Things (IIoT) in manufacturing. Industrialists and Manufacturers are already taking part in this transformation by integrating both new and existing Information and Operational Technologies (IT & OT). IIoT is fairly a new concept for industries, and it is presenting a huge opportunity in helping enterprises to operate more safely and productively while improving efficiency and reducing costs. The study was conducted to explore the benefits of IIoT in engineering and manufacturing industries, to analyse the various challenges on IIoT and to identify the ways to overcome the challenges of IIoT. This paper analyses how IIoT strategy facilitates to increase customer value, creates different opportunities for competitive advantage, and transform the business process to increase profit in industries. Secondary data was collected from web sources and journals to identify the benefits and challenges on the implementation of IIoT. Interviews with industry experts were conducted during October 2018 to obtain their opinion towards employment of IoT and IIoT technology in the engineering industries. As this paper concentrates only on bringing out the possibilities of implementing IIoT in engineering and manufacturing industries, this study is basically done as an exploratory research.
The purpose of this paper is to determine the influence of the factors of industrial and manufacturing engineering on quality of services that are provided in digital legal proceedings of the Asia-Pacific region, based on Big Data, blockchain, and AI. The authors model the influence of the factors of industrial and manufacturing engineering on quality of legal proceedings in countries of the Asia-Pacific region with the help of correlation analysis. Simplex method is used for determining the optimal influence of the factors of industrial and manufacturing engineering on quality of legal proceedings in countries of the Asia-Pacific region. It is determined that the potential of increase of quality of services of digital legal proceedings based on managing the factors of industrial and manufacturing engineering is more vivid in developing countries (33.55%) than in developed countries (9.36%). The authors reflect a new view on the prospects of development of legal proceedingsfrom the position of consumers' interests' protection, emphasizing on quality of the provided public services. Due to this, a new, alternative approach to state management of development of the legal proceedings system is developed; instead of increase of regulation, it envisages de-regulation and marketization of legal proceedings. An original approach to managing the quality of services of digital legal proceedings is offered, which is based on managing the factors of industrial and manufacturing engineering.
Unrivaled coverage of a broad spectrum of industrial engineering concepts and applicationsThe Handbook of Industrial Engineering, Third Edition contains a vast array of timely and useful methodologies for achieving increased productivity, quality, and competitiveness and improving the quality of working life in manufacturing and service industries. This astoundingly comprehensive resource, now available in a three-volume set, also provides a cohesive structure to the discipline of industrial engineering with four major classifications: technology; performance improvement management; management, planning, and design control; and decision-making methods. Completely updated and expanded to reflect nearly a decade of important developments in the field, this Third Edition features a wealth of new information on project management, supply-chain management and logistics, and systems related to service industries. Other important features of this essential reference include: More than 1,000 helpful tables, graphs, figures, and formulas Step-by-step descriptions of hundreds of problem-solving methodologiesHundreds of clear, easy-to-follow application examples Contributions from 176 accomplished international professionals with diverse training and affiliations More than 4,000 citations for further readingVolume 1 includes the list of advisory board members, the contributors, Foreword by John Powers, Preface by Gavriel Salvendy, the table of contents, Section 1: Industrial Engineering Function and Skills, and Section II: Technology. Volume 2 includes Section III: Performance Improvement Management and Section IV: Management, Planning, Design, and Control.Volume 3 includes Section V: Methods for Decision Making and the comprehensive Author and Subject Index.The Handbook of Industrial Engineering, Third Edition is an immensely useful one-stop resource for industrial engineers and technical support personnel in corporations of any size; continuous process and discrete part manufacturing industries; and all types of service industries, from healthcare to hospitality, and from retailing to finance.
This work examines how AI, especially agentic systems, is being adopted in engineering and manufacturing workflows, what value it provides today, and what is needed for broader deployment. This is an exploratory and qualitative state-of-practice study grounded in over 30 interviews across four stakeholder groups (large enterprises, small/medium firms, AI developers, and CAD/CAM/CAE vendors). We find that near-term AI gains cluster around structured, repetitive work and data-intensive synthesis, while higher-value agentic gains come from orchestrating multi-step workflows across tools. Adoption is constrained less by model capability than by fragmented and machine-unfriendly data, stringent security and regulatory requirements, and limited API-accessible legacy toolchains. Reliability, verification, and auditability are central requirements for adoption, driving human-in-the-loop frameworks and governance aligned with existing engineering reviews. Beyond technical barriers there are also organizational ones: a persistent AI literacy gap, cultural heterogeneity, and governance structures that have not yet caught up with agentic capabilities. Together, the findings point to a staged p
Requirements engineering in Industry 4.0 faces critical challenges with heterogeneous, unstructured documentation spanning technical specifications, supplier lists, and compliance standards. While retrieval-augmented generation (RAG) shows promise for knowledge-intensive tasks, no prior work has evaluated RAG on authentic industrial RE workflows using comprehensive production-grade performance metrics. This paper presents a comprehensive empirical evaluation of RAG for industrial requirements engineering automation using authentic automotive manufacturing documentation comprising 669 requirements across four specification standards (MBN 9666-1, MBN 9666-2, BQF 9666-5, MBN 9666-9) spanning 2015-2023, plus 49 supplier qualifications with extensive supporting documentation. Through controlled comparisons with BERT-based and ungrounded LLM approaches, the framework achieves 98.2% extraction accuracy with complete traceability, outperforming baselines by 24.4% and 19.6%, respectively. Hybrid semantic-lexical retrieval achieves MRR of 0.847. Expert quality assessment averaged 4.32/5.0 across five dimensions. The evaluation demonstrates 83% reduction in manual analysis time and 47% cost s
Automated surface defect detection is critical for ensuring rigorous quality control in high-speed manufacturing environments. While deep learning models offer remarkable accuracy, deploying them on resource-constrained edge hardware without introducing significant latency remains a persistent challenge. This paper presents Industrial-YOLO, an edge-optimized framework built upon a fine-tuned YOLOv8 architecture specifically engineered for real-time industrial defect detection. We conduct a systematic benchmark utilizing the NEU surface defect database for steel sheets and the MVTec AD dataset, supplemented with custom automotive manufacturing extensions representing real-world structural anomalies (scratches, pits, and inclusions). To bridge the gap between algorithmic complexity and edge hardware constraints, target-specific optimizations are introduced via TensorRT and OpenVINO acceleration engines. Experimental results demonstrate that Industrial-YOLO achieves a high-velocity inference speed exceeding 120 FPS on the NVIDIA Jetson Orin platform while maintaining an exceptional mean Average Precision (mAP) of 98.5%. The proposed framework showcases highly robust, zero-latency perf
In the rapidly evolving field of software engineering, the skills required of graduates entering the job market are constantly changing. Several studies have identified a gap between the skills taught in university curricula and those demanded by the software engineering industry. This chapter investigates the technical skill and expertise gap between higher education institutions (HEIs) and the UK software engineering industry by mapping job descriptions to the skills included in computer science degree programmes. A custom web scraping and text analysis tool, utilising fuzzy matching, was developed to extract and categorise skills from 300 job postings and undergraduate curricula from 30 UK universities. The analysis showed that the curricula place a strong emphasis on Programming Languages (18%) and Database Management (12.83%). In contrast, the industry s most frequently requested skill category is Software Design and Planning, which appears in approximately 88.68% of job descriptions, highlighting its critical importance. General Programming Language and System Structures also show strong demand, present in over 78.30% and 66.04% of postings, respectively. The mapping indicate
Reverse engineering can be used to derive a 3D model of an existing physical part when such a model is not readily available. For parts that will be fabricated with subtractive and formative manufacturing processes, existing reverse engineering techniques can be readily applied, but parts produced with additive manufacturing can present new challenges due to the high level of process-induced distortions and unique part attributes. This paper introduces an integrated 3D scanning and process simulation data-driven framework to minimize distortions of reverse-engineered additively manufactured components. This framework employs iterative finite element simulations to predict geometric distortions to minimize errors between the predicted and measured geometrical deviations of the key dimensional characteristics of the part. The effectiveness of this approach is then demonstrated by reverse engineering two Inconel-718 components manufactured using laser powder bed fusion additive manufacturing. This paper presents a remanufacturing process that combines reverse engineering and additive manufacturing, leveraging geometric feature-based part compensation through process simulation. Our ap
Software engineering conferences bring together thousands of academicians and software practitioners so that academic research and professional practices can influence each other. In essence, a symbiotic relationship exists between the research community and the software industry, which must be maintained, nurtured and re-examined periodically. Given the major AI breakthroughs (e.g., LLMs) and large-scale adoption of AI by the software industry, a re-examination of the relationship between academia and the SE industry is highly warranted. In this position paper, we argue that the software engineering community is deeply concerned about its research impact and relevance to industry practices. By conducting an empirical study using the survey responses from the SE community, we not only provide compelling evidence supporting our position but also propose new calls for action and reforms in SE, and thus envision a new future for the software engineering community.
Manufacturing has evolved and become more automated, computerised and complex. In this paper, the origin, current status and the future developments in manufacturing are disused. Smart manufacturing is an emerging form of production integrating manufacturing assets of today and tomorrow with sensors, computing platforms, communication technology, control, simulation, data intensive modelling and predictive engineering. It utilises the concepts of cyber-physical systems spearheaded by the internet of things, cloud computing, service-oriented computing, artificial intelligence and data science. Once implemented, these concepts and technologies would make smart manufacturing the hallmark of the next industrial revolution. The essence of smart manufacturing is captured in six pillars, manufacturing technology and processes, materials, data, predictive engineering, sustainability and resource sharing and networking. Material handling and supply chains have been an integral part of manufacturing. The anticipated developments in material handling and transportation and their integration with manufacturing driven by sustainability, shared services and service quality and are outlined. The future trends in smart manufacturing are captured in ten conjectures ranging from manufacturing digitisation and material-product-process phenomenon to enterprise dichotomy and standardisation.
An attack taxonomy offers a consistent and structured classification scheme to systematically understand, identify, and classify cybersecurity threat attributes. However, existing taxonomies only focus on a narrow range of attacks and limited threat attributes, lacking a comprehensive characterization of manufacturing cybersecurity threats. There is little to no focus on characterizing threat actors and their intent, specific system and machine behavioral deviations introduced by cyberattacks, system-level and operational implications of attacks, and potential countermeasures against those attacks. To close this pressing research gap, this work proposes a comprehensive attack taxonomy for a holistic understanding and characterization of cybersecurity threats in manufacturing systems. Specifically, it introduces taxonomical classifications for threat actors and their intent and potential alterations in system behavior due to threat events. The proposed taxonomy categorizes attack methods/vectors and targets/locations and incorporates operational and system-level attack impacts. This paper also presents a classification structure for countermeasures, provides examples of potential co
This book provides the most advanced, comprehensive, and balanced coverage on the market of the technical and engineering aspects of automated production systems. It covers all the major cutting-edge technologies of production automation and material handling, and how these technologies are used to construct modern manufacturing systems. Manufacturing Operations; Industrial Control Systems; Sensors, Actuators, and Other Control System Components; Numerical Control; Industrial Robotics; Discrete Control Using Programmable Logic Controllers and Personal Computers; Material Transport Systems; Storage Systems; Automatic Data Capture; Single Station Manufacturing Cells; Group Technology and Cellular Manufacturing; Flexible Manufacturing Systems; Manual Assembly Lines; Transfer Lines and Similar Automated Manufacturing Systems; Automated Assembly Systems; Statistical Process Control; Inspection Principles and Practices; Inspection Technologies; Product Design and CAD/CAM in the Production System; Process Planning and Concurrent Engineering; Production Planning and Control Systems; and Lean Production and Agile Manufacturing. For anyone interested in Automation, Production Systems, and Computer-Integrated Manufacturing.
Sustainable manufacturing requires simultaneous consideration of economic, environmental, and social implications associated with the production and delivery of goods. Fundamentally, sustainable manufacturing relies on descriptive metrics, advanced decision-making, and public policy for implementation, evaluation, and feedback. In this paper, recent research into concepts, methods, and tools for sustainable manufacturing is explored. At the manufacturing process level, engineering research has addressed issues related to planning, development, analysis, and improvement of processes. At a manufacturing systems level, engineering research has addressed challenges relating to facility operation, production planning and scheduling, and supply chain design. Though economically vital, manufacturing processes and systems have retained the negative image of being inefficient, polluting, and dangerous. Industrial and academic researchers are re-imagining manufacturing as a source of innovation to meet society's future needs by undertaking strategic activities focused on sustainable processes and systems. Despite recent developments in decision making and process- and systems-level research, many challenges and opportunities remain. Several of these challenges relevant to manufacturing process and system research, development, implementation, and education are highlighted.
Topological Data Analysis (TDA) is a discipline that applies algebraic topology techniques to analyze complex, multi-dimensional data. Although it is a relatively new field, TDA has been widely and successfully applied across various domains, such as medicine, materials science, and biology. This survey provides an overview of the state of the art of TDA within a dynamic and promising application area: industrial manufacturing and production, particularly within the Industry 4.0 context. We have conducted a rigorous and reproducible literature search focusing on TDA applications in industrial production and manufacturing settings. The identified works are categorized based on their application areas within the manufacturing process and the types of input data. We highlight the principal advantages of TDA tools in this context, address the challenges encountered and the future potential of the field. Furthermore, we identify TDA methods that are currently underexploited in specific industrial areas and discuss how their application could be beneficial, with the aim of stimulating further research in this field. This work seeks to bridge the theoretical advancements in TDA with the p
Introduction. PART I: MATERIAL PROPERTIES AND PRODUCT ATTRIBUTES.The Nature of Materials. Mechanical Properties of Materials. Physical Properties of Materials. Dimensions, Tolerances, and Surfaces. PART II: ENGINEERING MATERIALS. Metals. Ceramics. Polymers.Composite Materials. PART III: SOLIDIFICATION PROCESSES. Fundamentals of Metal Casting. Metal Casting Processes. Glassworking. Shaping Processes for Plastics. Rubber Processing Technology. Shaping Processes for Polymer Matrix Composites. PART IV: PARTICULATE PROCESSING OF METALS AND CERAMICS. Powder Metallurgy. Processing of Ceramics and Cermets.PART V: METAL FORMING AND SHEET METALWORKING. Fundamentals of Metal Forming. Bulk Deformation Processes in Metal Working.Sheet Metal Working. PART VI: MATERIAL REMOVAL PROCESSES. Theory of Metal Machining.Machining Operations and Machine Tools. Cutting Tool Technology. Economic and Product Design Considerations in Machining. Grinding and Other Abrasive Processes. Nontraditional Machining and Thermal Cutting Processes. PART VII: PROPERTY ENHANCING AND SURFACE PROCESSING OPERATIONS. Heat Treatment of Metals. Cleaning and Surface Treatments. Coating and Deposition Processes. PART VIII: JOINING AND ASSEMBLY PROCESSES. Fundamentals of Welding.Welding Processes. Brazing, Soldering,and Adhesive Bonding. Mechanical Assembly. PART IX: SPECIAL PROCESSING AND ASSEMBLY TECHNOLOGIES.Rapid Prototypiing. Processing of Integrated Circuits. Electronics Assembly and Packaging. Microfabrication Technologies. PART X: MANUFACTURING SYSTEMS. Numerical Control and Industrial Robotics. Group Technology and Flexible Manaufacturing Systems. Production Lines. PART XI: MANUFACTURING SUPPORT SYSTEMS. Manufacturing Engineering. Production Planning and Control. Quality Control. Measurement and Inspection. Index.