Wireless Sensor Node for Industry 4.0

Internet of thing (IOT) is new trend in the manufacturing Industries. By making use of IOT it is possible to connect all parts of the production process like machines, products and the systems. Industry 4.0 relies heavily on the Internet of Things - objects embedded with technology that can communicate with IT systems and be detected by sensors. The main intension of “Industry 4.0” approach is to achieving intelligent planning, production, manufacturing, maintenance, and servicing in the industry. This paper presents the method to improve the production and maintenance in the manufacturing industries by using wireless sensor node

The future of software engineering: Visions of 2025 and beyond

In the current technological scenario of the industry and businesses, there has been increasing need of software within systems and also an increasing demand being put onto software-intensive systems. This in effect will lead to a significant evolution of software engineering processes over the next twenty years. This is due to the fact of emerging technological advancements like Industry 4.0 and Internet of Things in the IT field, among other new developments. This paper addresses and tries to analyses the key research challenges being faced by the software engineering field and articulates information that is derived from the key research specializations within software engineering. The paper analyses the past and current trends in software engineering. The future of software engineering is also looked with respect to Industry 4.0 which including emerging technological platforms like Internet of Things. The societal impact aspect of future trends in software engineering is also addressed in this paper

How to Sustainably Implement a Smart Factory through a Socio-Technical perspective: an evolutionary framework

In recent years Industry 4.0, in particular through Smart Factory, promises a revolution in manufacturing due to the digitization, automation and virtualization of all organization processes. However, the requirements for a sustain- able implementation of Smart Factory go beyond technological and processual issues. The orientation of technology management strategy with the organizational goals, infrastructure, culture, processes and people should be judiciously carried out. Adopting a socio-technical perspective based on six-dimensional model, this study aims at developing a framework that describes the evolutionary path to design a sustainable architecture for implementation of a Smart Factory. We argue that the implementation of Smart Factory is, and should be, an incremental process. In particular, we identify three evolutionary steps for implementation of the Smart Factory, namely Aspiration, Awareness and Maturity. Finally, the framework is tested through an exploratory case study

Industry 4.0 as a Key Enabler toward Successful Implementation of Total Quality Management Practices

Industry 4.0 refers to the new technological development occurred at the industrial production systems. It evolved as a result of integrating Internet of Things, Cyber-Physical Systems, Big-Data, Artificial Intelligence, and Cloud Computing in the industrial systems. This integration aided new capabilities to achieve a higher level of business excellence, efficiency, and effectiveness. Total Quality Management (TQM) is a managerial approach to achieve an outstanding business excellence. There are several approaches to apply TQM principles at any organization. Industry 4.0 could be utilized as a key enabler for TQM especially by integrating its techniques with the TQM best practices. This paper suggests a theoretical framework for integrating Industry 4.0 features with the TQM principles (according to ISO 9000:2015 standards family) in order to open the door for further research to address the real impact of utilizing Industry 4.0 for serving the TQM implementation approaches

Quality 4.0 – An Analysis from the Perspective of Method Engineers in Quality Management

“Quality 4.0” is a central research field of quality management in times of industry 4.0. However, the topic is rather new, and a profound theoretical foundation of the concept does not yet exist. Hence, it is not clear whether existing quality management methods can be smoothly transferred to industry 4.0 settings or not. Moreover, companies often lack the time to design quality management approaches for this field and to critically scrutinize the skills needed by quality managers for quality 4.0. Based on a structured literature review, this study takes the perspective of method engineers in quality management. It provides an overview of those quality management methods and quality techniques that are frequently discussed in quality 4.0 literature and seem promising for quality projects in industry 4.0 settings. In this way, insights for method engineers are derived for the purpose of method construction for quality 4.0

Development of a low cost machine vision based quality control system for a learning factory

CITATION: Louw, L. & Droomer, M. 2019. Development of a low cost machine vision based quality control system for a learning factory. Procedia Manufacturing, 31:264-269, doi:10.1016/j.promfg.2019.03.042.The original publication is available at https://www.sciencedirect.comENGLISH ABSTRACT: Learning Factories provide a promising environment for developing the competencies required from a future workforce to apply and integrate technologies associated with digitalised production environments and cyber-physical systems. This paper describes a student project for the development and implementation of a low cost machine vision based quality control system within a Learning Factory. A prototype system was developed using low cost hardware and open source software freely available. The system will be used towards further research and development of more intelligent manufacturing systems within the Learning Factory, based on machine vision. A second benefit was student competency development through self-learning and experimentation. It serves to illustrate how the education as well as research goals of a Learning Factory can be addressed simultaneously through student projects.https://www.sciencedirect.com/science/article/pii/S2351978919304068Publisher's versio

Exploring industry 4.0 technologies to enable circular economy practices in a manufacturing context: a business model proposal.

Purpose - The purpose of this study was to explore how rising technologies from Industry 4.0 can be integrated with circular economy (CE) practices to establish a business model that reuses and recycles wasted material such as scrap metal or e-waste Design/methodology/approach – The qualitative research method was deployed in three stages. Stage one was a literature review of concepts, successful factors, and barriers related to the transition towards a CE along with sustainable supply chain management, smart production systems, and additive manufacturing. Stage two comprised a conceptual framework to integrate and evaluate the synergistic potential among these concepts. Finally, stage three validated the proposed model by collecting rich qualitative data based on semi-structured interviews with managers, researchers, and professors of operations management to gather insightful and relevant information. Findings – The outcome of the study is the recommendation of a circular model to reuse scrap electronic devices, integrating web technologies, reverse logistics, and additive manufacturing to support CE practices. Results suggest a positive influence from improving business sustainability by reinserting waste into the supply chain to manufacture products on demand. Research implications/originality – The impact of reusing wasted materials to manufacture new products is relevant to minimizing resource consumption and negative environmental impacts. Furthermore, it avoids hazardous materials ending up in landfills or in the oceans, seriously threatening life in ecosystems. In addition, reuse of wasted material enables the development of local business networks that generate jobs and improve economic performance.N/

An empirical study into the limitations and emerging trends of Six Sigma in manufacturing and service organisations

Purpose: The purpose of this paper is to carry out an empirical study of the limitations and emerging trends of Six Sigma in manufacturing and service companies.Design/methodology/approach: The authors developed an online survey instrument based on the existing literature addressing the current limitations and emerging trends of Six Sigma in manufacturing and service companies. In this study, 75 Six Sigma Master Black Belts, 39 Black Belts and 12 Green Belts from large manufacturing and service companies participated; each of whom is familiar with the Six Sigma topics.Findings: This study reports the top 5 limitations and emerging trends of Six Sigma from the viewpoints of subject matter experts from large manufacturing and service companies from over 20 countries. The main finding is that the top 4 limitations were identical for both manufacturing and service companies. These limitations include: the integration of Six Sigma with Big Data, the use of Six Sigma in small medium and micro-enterprises, an over emphasis of Six Sigma on variability reduction and the poor implementation of Six Sigma and its resultant negative impact on employee satisfaction.Practical implications: In order to sustain Six Sigma initiatives in organisations, the authors argue that the limitations and emerging trends of this powerful business strategy should be understood and appropriate remedial strategies developed to address said limitations.Originality/value: To the best of the authors’ knowledge, this is the first empirical study to examine the limitations and emerging trends of Six Sigma in both manufacturing and service organisations. Moreover, the findings of the study can be very beneficial to many organisations.</p

A review of the meanings and the implications of the Industry 4.0 concept

The global industrial landscape has changed deeply in the last few years due to successive technological developments and innovations in manufacturing processes. The Industry 4.0 concept has emerged and the academic literature has paid an increased attention to this topic, which remains non-consensual or ill defined. In this research, a literature review is made to understand this concept in its technological dimension, and to comprehend its impacts. This new industrial paradigm brings together the digital and physical worlds through the Cyber-Physical Systems enhanced by Internet of Things and it is expected that this novel has consequences on industry, markets and economy, improving production processes and increasing productivity, affecting the whole product lifecycle, creating new business models, changing the work environment and restructuring the labor market. Therefore, this paper focuses on Industry 4.0 concept and contributes for its clarification and further understanding about the importance and implications of this complex technological system.This work has been supported by COMPETE: POCI-01-0145-FEDER-007043 and FCT – Fundação para a Ciência e Tecnologia within the Project Scope: UID/CEC/00319/2013.info:eu-repo/semantics/publishedVersio