Systematic analysis of needs and requirements for the design of smart manufacturing systems in SMEs☆

Abstract With the increasing trend of the Fourth Industrial Revolution, also known as Industry 4.0 or smart manufacturing, many companies are now facing the challenge of implementing Industry 4.0 methods and technologies. This is a challenge especially for small and medium-sized enterprises, as they have neither sufficient human nor financial resources to deal with the topic sufficiently. However, since small and medium-sized enterprises form the backbone of the economy, it is particularly important to support these companies in the introduction of Industry 4.0 and to develop appropriate tools. This work is intended to fill this gap and to enhance research on Industry 4.0 for small and medium-sized enterprises by presenting an exploratory study that has been used to systematically analyze and evaluate the needs and translate them into a final list of (functional) requirements and constraints using axiomatic design as scientific approach

Sustainable Enterprise Design 4.0: Addressing Industry 4.0 Technologies from the Perspective of Sustainability

Abstract The introduction of Industry 4.0 and sustainability in production is currently on everyone's mind. However, companies face difficulties to address these trends in their long-term enterprise strategy and design. Industry 4.0 promises strategic advantages for companies in many respects, but there is a lack of instruments and concepts for integrating emerging technologies in an overall enterprise system design. Similarly, the multiple perspectives regarding economic, environmental and social sustainability provide a framework for thinking about a strategy for sustainable enterprise design. Based on the three principles presented in this paper for Sustainable Enterprise Design, this article aims to present an approach to better address sustainability as well as Industry 4.0 in terms of a long-term strategic, enterprise design that is sustainable. As a result, a list of needs, functional requirements as well as possible Industry 4.0 physical solutions is proposed to achieve a long-term sustainable enterprise design. The consequence of the perspective of an enterprise as a system that can be designed provides a rigorous approach that takes advantage of Industry 4.0 technologies and the multiple perspectives and candidate physical solutions that the research community offers

Emerging research fields in safety and ergonomics in industrial collaborative robotics: A systematic literature review

Abstract Human–robot collaboration is a main technology of Industry 4.0 and is currently changing the shop floor of manufacturing companies. Collaborative robots are innovative industrial technologies introduced to help operators to perform manual activities in so called cyber-physical production systems and combine human inimitable abilities with smart machines strengths. Occupational health and safety criteria are of crucial importance in the implementation of collaborative robotics. Therefore, it is necessary to assess the state of the art for the design of safe and ergonomic collaborative robotic workcells. Emerging research fields beyond the state of the art are also of special interest. To achieve this goal this paper uses a systematic literature review methodology to review recent technical scientific bibliography and to identify current and future research fields. Main research themes addressed in the recent scientific literature regarding safety and ergonomics (or human factors) for industrial collaborative robotics were identified and categorized. The emerging research challenges and research fields were identified and analyzed based on the development of publications over time (annual growth)

A Review of Further Directions for Artificial Intelligence, Machine Learning, and Deep Learning in Smart Logistics

Industry 4.0 concepts and technologies ensure the ongoing development of micro- and macro-economic entities by focusing on the principles of interconnectivity, digitalization, and automation. In this context, artificial intelligence is seen as one of the major enablers for Smart Logistics and Smart Production initiatives. This paper systematically analyzes the scientific literature on artificial intelligence, machine learning, and deep learning in the context of Smart Logistics management in industrial enterprises. Furthermore, based on the results of the systematic literature review, the authors present a conceptual framework, which provides fruitful implications based on recent research findings and insights to be used for directing and starting future research initiatives in the field of artificial intelligence (AI), machine learning (ML), and deep learning (DL) in Smart Logistics

Methodology for the definition of the optimal assembly cycle and calculation of the optimized assembly cycle time in human-robot collaborative assembly

AbstractIndustrial collaborative robotics is an enabling technology and one of the main drivers of Industry 4.0 in industrial assembly. It allows a safe physical and human-machine interaction with the aim of improving flexibility, operator's work conditions, and process performance at the same time. In this regard, collaborative assembly is one of the most interesting and useful applications of human-robot collaboration. Most of these systems arise from the re-design of existing manual assembly workstations. As a consequence, manufacturing companies need support for an efficient implementation of these systems. This work presents a systematical methodology for the design of human-centered and collaborative assembly systems starting from manual assembly workstations. In particular, it proposes a method for task scheduling identifying the optimal assembly cycle by considering the product and process main features as well as a given task allocation between the human and the robot. The use of the proposed methodology has been tested and validated in an industrial case study related to the assembly of a touch-screen cash register. Results show how the new assembly cycle allows a remarkable time reduction with respect to the manual cycle and a promising value in terms of payback period

Anthropocentric perspective of production before and within Industry 4.0

Abstract This paper presents a systematic literature review (SLR) of the anthropocentric perspective of production before and after (or, better, within) Industry 4.0. We identify central research clusters regarding traditional Anthropocentric Production Systems (APS) and Anthropocentric Cyber Physical Production Systems. By comparing the two perspectives, we are able to analyse new emerging paradigms in anthropocentric production caused by Industry 4.0. We further make prediction of the future role of the human operator, his needed knowledge and capabilities and how assistance systems support the Operator 4.0. Our paper gives a brief outlook of current and needed future research. It builds grounds for further scholarly discussion on the role of humans in the factory of the future

business model engineering for distributed manufacturing systems

Abstract Distributed Manufacturing Systems (DMS) and collaborative, decentralized production networks are enablers to establish sustainable and high-competitive value chains. To support the diffusion of DMS, the systematic development of new business models for DMS should be considered in an early stage of forming such value chains. This paper introduces an engineering-based approach to develop and design new business models based on a distinction of four business model elements and using a three level model for designing, planning and managing operations to achieve production excellence in each production unit and ensure strategic probability to enhance implemented DMS to the next evolutionary stages

The way from Lean Product Development (LPD) to Smart Product Development (SPD)

Abstract Lean Product Development (LPD) is the application of lean principles to product development, aiming to develop new or improved products that are successful in the market. LPD deals with the complete process from gathering and generating ideas, through assessing potential success, to developing concepts, evaluating them to create a best concept, detailing the product, testing/developing it and handing over to manufacture. With the beginning of the fourth Industrial Revolution (Industrial 4.0) and the rising efforts to realize a smart factory environment, also product development has to perform a substantial transformation. This paper firstly describes the concept of Lean Product Development as well as new requirements for an intelligent and Smart Product Development (SPD) through the introduction of modern Industry 4.0 related technologies. Based on Axiomatic Design methodology, a set of guidelines for the design of Lean Product Development Processes is presented. These guidelines are linked with concepts from Industry 4.0 in Engineering, showing how a lean and smart product development process can be achieved by the use of advanced and modern technologies and instruments

Critical Factors for Introducing Lean Product Development to Small and Medium sized Enterprises in Italy

Abstract Small and medium sized enterprises are the backbone of many economies. Especially in Italy SME's play a major role in the economic system. In the last years many lean methods and approaches were introduced successfully also in small and medium sized enterprises. After a successful introduction in manufacturing the lean approach swapped also on other indirect areas such as engineering and product development. Actually in research we can find only few research on the application of Lean in the R&D departments of SME's. The novelty of this paper is to provide a survey based evaluation of applicability, benefits as well as critical factors of Lean in SME product development. In the survey 54 Italian SME's were asked for their opinion. Further, respondents gave a statement on the introduction of emerging Industry 4.0 techniques in product development and how they can influence the effect of Lean in product development. The main results are that numerous Lean methods can be introduced very quickly promising high potential for improvements and that Lean methods combined with Industry 4.0 technologies act like a booster for efficiency optimization in product development

Study of the impact of projection-based assistance systems for improving the learning curve in assembly processes

Abstract With the introduction of Industry 4.0 the use of worker assistance systems is getting more and more important. Assistance systems should support operators to increase efficiency and to reduce physical and mental stress and thus increase ergonomics of the work. In this paper, we investigate the impact of a projection-based worker assistance system conducting lab experiments simulating a ramp-up situation of a new product in assembly. The specific aim is the investigation of the impact of such systems in assembly for improving the learning curve, when products are changing. The study shows the results of a comparison between the assembly process with traditional worker instructions and the use of cognitive assistance systems to project instructions on the workplace