Industry 4.0: Adoption challenges and benefits for SMEs

The new industrial revolution called Industry 4.0 imposes new challenges to the research community. One of the main issues in Industry 4.0 is the management of the huge amount of information exchan...

Modelling and quantification of industry 4.0 manufacturing complexity based on information theory: a robotics case study

Industry 4.0 can be the starting point for implementation projects as a low-risk entry into an adapted digitization strategy. In larger companies, comprehensive digitization initiatives are already integrated into the central corporate strategy, while smaller companies often have problems putting the Industry 4.0 paradigms into practice. As the backbone of the economy, small- and medium-sized enterprises (SMEs) have an enormous leverage effect, which is why it is crucial to develop specific concepts for smaller companies. Regardless of the size of a company, a digital transformation strategy offers opportunities for growth and sustainable competitiveness. This chapter will give an introductory overview of Industry 4.0 as the fourth industrial revolution and discuss the role of SMEs in this transition towards the digital transformation.

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SME 4.0: The Role of Small- and Medium-Sized Enterprises in the Digital Transformation

By reconfiguring your traditional assembly lines into production cells based on one-piece flow, you can drastically reduce your lead time, staffing requirements, and number of defects. Kenichi Sekine studied under the late Shigeo Shingo and is responsible for many recent advances in the deployment of the Toyota Production System in Japan. In this comprehensive book, Sekine provides an in-depth education into the why's and how's of the restructuring process. Sekine first examines the basic principles of process flow building, then offers detailed case studies of how various industries designed unique one-piece flow systems (parallel, L-shaped, and U-shaped floor plans) to meet their particular needs. "One-Piece Flow" describes each step in the process of establishing one-piece flow and: provides ample 'test your skills' worksheets that guide you through the solution of problems; and, includes over 300 illustrations and 14 single-page case studies that show how to cut assembly personnel in various industries. With this book, plant managers will learn how to eliminate overstaffing waste and build a multi-skilled work force equipped to support JIT manufacturing.The book includes: basic concept of one-piece production; case studies; process razing techniques U-shaped cells for assembly lines; techniques for removing waste from factories; stablishing one-piece flow at a factory that produces small lots on a customer-order basis 'Single' delivery at MYNAC.

One-piece flow : cell design for transforming the production process

The traditional production paradigm of large batch production does not offer flexibility toward satisfying the requirements of individual customers. A new generation of smart factories is expected to support new multivariety and small-batch customized production modes. For this, artificial intelligence (AI) is enabling higher value-added manufacturing by accelerating the integration of manufacturing and information communication technologies, including computing, communication, and control. The characteristics of a customized smart factory are: self-perception, operations optimization, dynamic reconfiguration, and intelligent decision-making. The AI technologies will allow manufacturing systems to perceive the environment, adapt to the external needs, and extract the process knowledge, including business models, such as intelligent production, networked collaboration, and extended service models. This article focuses on the implementation of AI in customized manufacturing (CM). The architecture of an AI-driven customized smart factory is presented. Details of intelligent manufacturing devices, intelligent information interaction, and construction of a flexible manufacturing line are showcased. The state-of-the-art AI technologies of potential use in CM, that is, machine learning, multiagent systems, Internet of Things, big data, and cloud-edge computing, are surveyed. The AI-enabled technologies in a customized smart factory are validated with a case study of customized packaging. The experimental results have demonstrated that the AI-assisted CM offers the possibility of higher production flexibility and efficiency. Challenges and solutions related to AI in CM are also discussed.

Artificial-Intelligence-Driven Customized Manufacturing Factory: Key Technologies, Applications, and Challenges

Industry 40 as a new manufacturing paradigm brings in a new wave of networked manufacturers and smart factories, which will determine future competitiveness of manufacturing companies The aim for researchers should thus be to generate and optimize innovative solutions for different types of producers including SMEs in order to support them in meeting the challenges of Industry 40 The paper presents the readiness self-assessment method and roadmap model as a tools to secure a consistent implementation of technologies and devices supporting smart logistics and smart production Proposed method has been applied by selected SMEs and it was proved that the model is easy to use in real production environment

Mapping Requirements and Roadmap Definition for Introducing I 4.0 in SME Environment

Characterising existing approaches to operational complexity, it can be stated that for those metrics are characterful different factors used as variables such as product structure, machine composi...

Development of operational complexity measure for selection of optimal layout design alternative

Manufacturing systems can be considered as a network of machines/workstations, where parts are produced in flow shop or job shop environment, respectively. Such network of machines/workstations can be depicted as a graph, with machines as nodes and material flow between the nodes as links. The aim of this paper is to use sequences of operations and machine network to measure static complexity of manufacturing processes. In this order existing approaches to measure the static complexity of manufacturing systems are analyzed and subsequently compared. For this purpose, analyzed competitive complexity indicators were tested on two different manufacturing layout examples. A subsequent analysis showed relevant potential of the proposed method.

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Novel Complexity Indicator of Manufacturing Process Chains and Its Relations to Indirect Complexity Indicators

Process modularity of mass customized manufacturing systems: principles, measures and assessment

The sharing economy is becoming increasingly popular in many sectors also thanks to the fact that not only young generation, but people of almost all ages are digitally literate, and therefore they readily participate in sharing economy practices. A very important part of their motivation comes from the knowledge that it is a great way to save money, but a no less important reason is the philosophical aspect, which is consistent with efforts to promote more sustainable consumption practices that prioritize access over ownership. The sharing economy has become a subject of interest not only among researchers and practitioners but also among policymakers and stakeholders who are concerned about the further extension of digital ecosystems. Fortunately, theorists from many fields, such as the commercial economy, gift economy, entrepreneurship, digital transformation, etc., pay due attention to this phenomenon. However, there is still room for focused exploration of this entrepreneurial and innovative approach from specific views in order to bring useful findings and insights on given issues. The intention of this study is to analyze the existing related literature and categorize sharing economy-based business models in relation to traditional business models. Potentially, this study can also contribute to a better understanding of the perspectives of the sharing economy in the transition of SMEs towards the Industry 4.0 paradigm.

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Zuzana Soltysova

Papers

Mapping Requirements and Roadmap Definition for Introducing I 4.0 in SME Environment

Development of operational complexity measure for selection of optimal layout design alternative

Novel Complexity Indicator of Manufacturing Process Chains and Its Relations to Indirect Complexity Indicators

Process modularity of mass customized manufacturing systems: principles, measures and assessment

Challenges of the Sharing Economy for SMEs: A Literature Review