Lean manual assembly 4.0: A systematic review

In a demand context of mass customization, shifting towards the mass personalization of products, assembly operations face the trade-off between highly productive automated systems and flexible manual operators. Novel digital technologies—conceptualized as Industry 4.0—suggest the possibility of simultaneously achieving superior productivity and flexibility. This article aims to address how Industry 4.0 technologies could improve the productivity, flexibility and quality of assembly operations. A systematic literature review was carried out, including 234 peer-reviewed articles from 2010–2020. As a result, the analysis was structured addressing four sets of research questions regarding (1) assembly for mass customization; (2) Industry 4.0 and performance evaluation; (3) Lean production as a starting point for smart factories, and (4) the implications of Industry 4.0 for people in assembly operations. It was found that mass customization brings great complexity that needs to be addressed at different levels from a holistic point of view; that Industry 4.0 offers powerful tools to achieve superior productivity and flexibility in assembly; that Lean is a great starting point for implementing such changes; and that people need to be considered central to Assembly 4.0. Developing methodologies for implementing Industry 4.0 to achieve specific business goals remains an open research topic

A review on predictive maintenance technique for nuclear reactor cooling system using machine learning and augmented reality

Reactor TRIGA PUSPATI (RTP) is the only research nuclear reactor in Malaysia. Maintenance of RTP is crucial which affects its safety and reliability. Currently, RTP maintenance strategies used corrective and preventative which involved many sensors and equipment conditions. The existing preventive maintenance method takes a longer time to complete the entire system’s maintenance inspection. This study has investigated new predictive maintenance techniques for developing RTP predictive maintenance for primary cooling systems using machine learning (ML) and augmented reality (AR). Fifty papers from recent referred publications in the nuclear areas were reviewed and compared. Detailed comparison of ML techniques, parameters involved in the coolant system and AR design techniques were done. Multiclass support vector machines (SVMs), artificial neural network (ANN), long short-term memory (LSTM), feed forward back propagation (FFBP), graph neural networks-feed forward back propagation (GNN-FFBP) and ANN were used for the machine learning techniques for the nuclear reactor. Temperature, water flow, and water pressure were crucial parameters used in monitoring a nuclear reactor. Image marker-based techniques were mainly used by smart glass view and handheld devices. A switch knob with handle switch, pipe valve and machine feature were used for object detection in AR markerless technique. This study is significant and found seven recent papers closely related to the development of predictive maintenance for a research nuclear reactor in Malaysia

Full, hybrid and platform complementarity: Exploring the industry 4.0 technology-performance link

Literature has increasingly recognized that manufacturing companies should implement a synergic bundle of solutions to fully exploit the potential of Industry 4.0 (I4.0), rather than opting for a scattered technological adoption. Enabling I4.0 technologies, such as cloud computing, artificial intelligence, and additive manufacturing, can be implemented through various combinations to achieve different impacts on a company's performance. But what are the possible ways of combining I4.0 technologies into bundles, and do these ways actually help to achieve a performance that outperforms the adoption of single technologies? This study aims to identify the potential patterns of the technological complementary of I4.0 by considering enabled applications and performance outcomes. We interviewed 13 Italian experts in the I4.0 field, and then combined the obtained information with secondary data collected from more than 150 I4.0 use cases, as well as from websites, reports and press releases. By adopting a systems theory lens, the results of the analysis have allowed us to identify the specific performance effects of both scattered and joint technological adoptions in different application areas. Interestingly, specific examples of I4.0 complementarities emerged, namely full, hybrid and platform complementarity. This study contributes to the growing research on I4.0 outcomes by extending the concept of technological complementary within the I4.0 context. Results show that bundles of technologies have a broader effect on performance than when the same technologies are adopted in isolation, but also that single technologies can impact specific applications and the overall performance of a firm via a systematic I4.0 transformation path

Robotization and digitalisation in the construction industry

Abstract. Industry 4.0 has emerged as a famous concept in the last few years to describe the significance of digitisation and robotization in the smart manufacturing environment. The advancements in robotics, digital software, and smart technologies have allowed a new wave in the construction industry. The construction industry is the major economic pillar and provides a significant impact on the overall GDP of the country. Despite the predominant pillar, it is considered as the poor innovator and late adopter of new technologies, which ends up with delays and cost overruns in their construction projects. Considering this aspect, the research emphasises the importance of adopting the latest technologies in the construction industry in order to enhance the productivity and efficiency of various processes. This study seeks to examine existing robotization and digitalisation practices in the leading construction companies and intends to provide the required improvement ideas in this research domain. The empirical results revealed that the majority of the case companies lack basis to implement the latest technologies in their construction activities. They believe that effective use of the available technologies is an asset, but it is a long process to be achieved. Thus, the thesis is concluded by providing the critical information regarding the adoption of latest technologies and proposes a framework that can help to enhance the robotization and digitisation practices to improve the performance of the construction activities. The mentioned framework mainly focusses on elements that this research found as a potential need for companies to implement. This framework has a future scope for validation and also key elements of the framework can be utilised for further research

Human factor in industry of the future - Knowledge acquisition and motivation

Industry of the future bases on people knowledge, creativeness and motivations. Although, the number of workers needed in factories of the future decreases, the requiremenets concerning employees skills have been increasing. The knowledge of employees determines the factory system quality and efficiency. The motivation of people determines continuous improvement and development realized by problems identification and elimination. Hence, adequate learning methods are required to be implemented to achieve the following goals: empower and motivate people. This paper presents chosen methods such as learning by doing, computer simulations and virtual reality which support knowledge acquisition by people being prepared for work in factories of the future. The presented methods also increase employee awareness concerning possibilities of improvements

tiphys an open networked platform for higher education on industry 4 0

Abstract Objective of Tiphys project is building an Open Networked Platform for the learning of Industry 4.0 themes. The project will create a Virtual Reality (VR) platform, where users will be able to design and create a VR based environment for training and simulating industrial processes but they will be able to study and select among a set of models in order to standardize the learning and physical processes as a virtual representation of the real industrial world and the required interactions so that to acquire learning and training capabilities. The models will be structured in a modular approach to promote the integration in the existing mechanisms as well as for future necessary adaptations. The students will be able to co-create their learning track and the learning contents by collaborative working in a dynamic environment. The paper presents the development and validation of the learning model, built on CONALI learning ontology. The concepts of the ontology will be detailed and the platform functions will be demonstrated on selected use cases

A Scoping Review on Virtual Reality-Based Industrial Training

The fourth industrial revolution has forced most companies to technologically evolve, applying new digital tools, so that their workers can have the necessary skills to face changing work environments. This article presents a scoping review of the literature on virtual reality-based training systems. The methodology consisted of four steps, which pose research questions, document search, paper selection, and data extraction. From a total of 350 peer-reviewed database articles, such as SpringerLink, IEEEXplore, MDPI, Scopus, and ACM, 44 were eventually chosen, mostly using the virtual reality haptic glasses and controls from Oculus Rift and HTC VIVE. It was concluded that, among the advantages of using this digital tool in the industry, is the commitment, speed, measurability, preservation of the integrity of the workers, customization, and cost reduction. Even though several research gaps were found, virtual reality is presented as a present and future alternative for the efficient training of human resources in the industrial field.This work was supported by Instituto Superior Tecnológico Victoria Vásconez Cuvi. The authors appreciate the opportunity to analyze topics related to this paper. The authors must also recognize the supported bringing by Universidad Tecnica de Ambato (UTA) and their Research and Development Department (DIDE) under project CONIN-P-256-2019, and SENESCYT by grants “Convocatoria Abierta 2011” and “Convocatoria Abierta 2013”

Using virtual reality and 3D industrial numerical models for immersive interactive checklists

At the different stages of the PLM, companies develop numerous checklist-based procedures involving prototype inspection and testing. Besides, techniques from CAD, 3D imaging, animation and virtual reality now form a mature set of tools for industrial applications. The work presented in this article develops a unique framework for immersive checklist-based project reviews that applies to all steps of the PLM. It combines immersive navigation in the checklist, virtual experiments when needed and multimedia update of the checklist. It provides a generic tool, independent of the considered checklist, relies on the integration of various VR tools and concepts, in a modular way, and uses an original gesture recognition. Feasibility experiments are presented, validating the benefits of the approach