Design Framework for Preparing Workforce Towards Industry 4.0 Implementation in Small and Medium-Sized Enterprises

Author(s):  
Sagil James ◽  
Anupam Shetty

Abstract The fourth industrial revolution, also known as Industry 4.0 is a new paradigm that is significantly influencing several manufacturing industries across the globe. Industry 4.0 synchronizes concepts such as Smart Manufacturing, Smart Factory, and the Internet of Things with existing factory automation technologies in order to improve value in manufacturing by monitoring key performance indicators and creates value in all manufacturing related aspects. Currently, several large companies industries have started early initiatives for implementing these technologies. However, small and medium-sized enterprises (SMEs) face massive challenges in adopting Industry 4.0 technologies. As the SMEs are evaluating their readiness for implementing the Industry 4.0 concepts, several challenges need to be addressed, including high initial investment, lack of standardization, data security, and lack of skilled labor. A strategic roadmap towards implementing the Industry 4.0 paradigms is still unclear in the SME sector as well as in academia. This research focuses on designing a framework for training/retraining the strong workforce for SMEs to enable Industry 4.0 adoption and implementation. The framework is created using qualitative research methods followed by the secondary data collection approach. The study suggests the use of a three-step implementation process consisting of 1) creating new jobs, 2) recruiting, and 3) retraining and retaining the talent. The results of this study are expected to create a platform to train the workforce for Industry 4.0, reduce skill gaps, and retain incumbent workers in the manufacturing sector.

Author(s):  
Sagil James ◽  
Anupam Shetty

Abstract The fourth industrial revolution, also known as Industry 4.0 is a new paradigm that is significantly influencing several manufacturing industries across the globe. Industry 4.0 synchronizes concepts such as Smart Manufacturing, Smart Factory, and the Internet of Things with existing factory automation technologies in order to improve value in manufacturing by monitoring key performance indicators and creates value in all manufacturing related aspects. Currently, several industries have started early initiatives of implementing these technologies. As the industries are evaluating their readiness for implementing the Industry 4.0 concepts, there are several challenges which need to be addressed including high initial investment, lack of standardization, data security and lack of skilled labor. A strategic roadmap towards implementing the Industry 4.0 paradigms is still unclear in the industry as well as in academia. This research develops an initial framework for the effective implementation of Industry 4.0 in the high technology manufacturing sectors in the Southern California region. The results of this study are expected to provide a platform to expand the opportunities of Industry 4.0 further and facilitate worldwide adoption.


2021 ◽  
Vol 2 (1) ◽  
pp. 1-9
Author(s):  
Pradeep Kumar

Sustainable manufacturing has been a popular topic of research for quite some time now. There are various concepts and ideas which have claimed to have a significant impact on sustainability of the manufacturing industry like lean, green and agile manufacturing. Industry 4.0 is the latest and by far the one with the maximum potential of changing the manufacturing sector forever. It is rightly called as “the fourth industrial revolution”. It is a wide concept which covers many state of the art technologies like the Internet of Things (IoT), Artificial Intelligence, Big Data, Augmented reality etc. But like every big revolution, it is to face many challenges also. In this review, we are looking at this ‘yet in infancy’ concept and its role in achieving a sustainable manufacturing sector as discussed by researchers. Different scholars have come up with different challenges to implementation of I4.0 which they thought to be of some significance. There is going to  review such challenges making a list of 13 such challenges. Then, it also throw some light on the new challenge faced by all of humanity in the form of SARS-CoV-2 pandemic and how it is affecting the manufacturing sector.


Author(s):  
Mohd Syaiful Rizal Abd Hamid ◽  
Nor Ratna Masrom ◽  
Nur Athirah Binti Mazlan

IR 4.0 is a new phase for the current trend of automation and data exchange in manufacturing industry that focuses on cloud computing, interconnectivity, the Internet of Things, machine learning, cyber physical learning and creating smart factory. The purpose of this article was to unveil the key factors of the IR 4.0 in Malaysian smart manufacturing context. Two key data collection methods were used: (1) primary data from the face-to-face interview (2) secondary data from the previous study. Significantly, five key factors of IR 4.0 consider for this study. Autonomous production lines, smart manufacturing practices, data challenge, process flexibility, and security. As a result, IR 4.0 for quality management practices might get high impact for the best performance assessment, which addressed in various ways; there are few studies in this area have been conducted in Malaysian manufacturing sector, and to recommend the best practices implemented from the managers’ perspectives. For scholars, this enhances their understanding and highlight opportunities for further research.


Author(s):  
Amlan Das*

We are amidst a noteworthy change with respect to the manner in which we make items, because of the digitization of assembling. This change is convincing to the point that it is being called Industry 4.0 to speak to the fourth insurgency that has happened in assembling. Industry 4.0 is flagging an adjustment in the conventional assembling scene. Otherwise called the Fourth Industrial Revolution, Industry 4.0 envelops three mechanical patterns driving this change: network, insight and adaptable robotization. Industry 4.0 portrays the developing pattern towards computerization and information trade in innovation and cycles inside the assembling business, including: The Internet of Things (IoT), The Industrial Internet of Things (IIoT), Cyber-physical Systems (CPS), Smart Manufacturing, Smart Factories, Cloud Computing, Additive Manufacturing, Big Data, Robotics, Cognitive Computing, Artificial Intelligence and Block chain and so forth. This mechanization makes an assembling framework whereby the machines in manufacturing plants are increased with remote network and sensors to screen and picture a whole creation cycle and settle on independent choices. In this paper we are worry about how aptitude and ability of human asset can be grown with the goal that we can conquer this pandemic circumstance effectively. Delicate abilities for taking care of these forthcoming new innovation inserted framework must be taken consideration and carefully instilled by human asset with the goal that simple smooth of efficiency just as hole crossing over of flexibly and request can be conceivable. Skill development should be considered as prioritizing factor for this.


Author(s):  
Maja Bärring ◽  
Björn Johansson ◽  
Goudong Shao

Abstract The manufacturing sector is experiencing a technological paradigm shift, where new information technology (IT) concepts can help digitize product design, production systems, and manufacturing processes. One of such concepts is Digital Twin and researchers have made some advancement on both its conceptual development and technological implementations. However, in practice, there are many different definitions of the digital-twin concept. These different definitions have created a lot of confusion for practitioners, especially small- and medium-sized enterprises (SMEs). Therefore, the adoption and implementation of the digital-twin concept in manufacturing have been difficult and slow. In this paper, we report our findings from a survey of companies (both large and small) regarding their understanding and acceptance of the digital-twin concept. Five supply-chain companies from discrete manufacturing and one trade organization representing suppliers in the automotive business were interviewed. Their operations have been studied to understand their current digital maturity levels and articulate their needs for digital solutions to stay competitive. This paper presents the results of the research including the viewpoints of these companies in terms of opportunities and challenges for implementing digital twins.


2018 ◽  
Vol 15 (4) ◽  
pp. 528-534
Author(s):  
Adriano Pereira ◽  
Eugênio De Oliveira Simonetto ◽  
Goran Putnik ◽  
Helio Cristiano Gomes Alves de Castro

Technological evolutions lead to changes in production processes; the Fourth Industrial Revolution has been called Industry 4.0, as it integrates Cyber-Physical Systems and the Internet of Things into supply chains. Large complex networks are the core structure of Industry 4.0: any node in a network can demand a task, which can be answered by one node or a set of them, collaboratively, when they are connected. In this paper, the aim is to verify how (i) network's connectivity (average degree) and (ii) the number of levels covered in nodes search impacts the total of production tasks completely performed in the network. To achieve the goal of this paper, two hypotheses were formulated and tested in a computer simulation environment developed based on a modeling and simulation study. Results showed that the higher the network's average degree is (their nodes are more connected), the greater are the number of tasks performed; in addition, generally, the greater are the levels defined in the search for nodes, the more tasks are completely executed. This paper's main limitations are related to the simulation process, which led to a simplification of production process. The results found can be applied in several Industry 4.0 networks, such as additive manufacturing and collaborative networks, and this paper is original due to the use of simulation to test this kind of hypotheses in an Industry 4.0 production network.


Author(s):  
Zelal Gültekin Kutlu

In this study, the periodical differences of industrial revolutions, which is one of the effects of technological developments in the industrial field, and the last stage of it are mentioned. With the latest industrial revolution called Industry 4.0, machines work in harmony with technology at every stage of industrial areas. This period, known as Industry 4.0 or the fourth industrial revolution, refers to the system in which the latest production technologies, automation systems, and the technologies that make up this system exchange data with each other. In addition to the information technologies and automation systems used in Industry 3.0, industrial production has gained a whole new dimension with the use of the internet. With internet networks, machines, operators, and robots now work in harmony. At this point, the concept of internet of objects becomes important. Therefore, another focus of the study is the concept of internet of objects. There are some assumptions about the uses, benefits, and future status of the internet of things.


2022 ◽  
pp. 1-18
Author(s):  
Ilknur Taştan Boz ◽  
Özden Ibrahimağaoğlu

Industries have undergone three fundamental transformation processes that were revolutionary. Following these processes, industries have been confronted with the phenomenon of Industry 4.0, known as the 4th Industrial Revolution, that is acknowledged as a new transformation process. The basic dynamics of this phenomenon include smart robots, simulation, the internet of things, cloud, additive manufacturing, and big data. It is of utmost importance for businesses that are involved in this process, that are new and trying to adapt to the process, to be prepared and adapt to the effects of Industry 4.0 dynamics. These dynamics lead to significant developments in business models, business processes, organizational structures, employees, and human resource processes. When Industry 4.0 and its dynamics are evaluated in general, businesses that follow the process and make necessary managerial adjustments will be ahead of the competition.


IoT ◽  
2020 ◽  
Vol 1 (1) ◽  
pp. 49-75
Author(s):  
Antonio Oliveira-Jr ◽  
Kleber Cardoso ◽  
Filipe Sousa ◽  
Waldir Moreira

Industry 4.0 and digital farming rely on modern communication and computation technologies such as the Internet of Things (IoT) to provide smart manufacturing and farming systems. Having in mind a scenario with a high number of heterogeneous connected devices, with varying technologies and characteristics, the deployment of Industry 4.0 and digital farming solutions faces innovative challenges in different domains (e.g., communications, security, quality of service). Concepts such as network slicing and Software-Defined Networking (SDN) provide the means for faster, simpler, scalable and flexible solutions in order to serve a wide range of applications with different Quality-of-Service (QoS) requirements. Hence, this paper proposes a lightweight slice-based QoS manager for non-3GPP IoT focusing on different use cases and their varying requirements and characteristics. Our focus in this work is on non-3GPP IoT unlicensed wireless technologies and not specifically the end-to-end network slice perspective as described in 5G standards. We implemented and evaluated different QoS models in distinct scenarios in a real experimental environment in order to illustrate the potential of the proposed solution.


2021 ◽  
Author(s):  
Chinedu Onyeme ◽  
Kapila Liyanage

The shift towards Industry 4.0 is a fundamental driver of improved changes observed in today’s business organizations. The difficulties in adapting to this new approach pose challenges for many companies especially in the oil and gas (O&G) upstream sector. To make this path much feasible for companies in this industry, Maturity Models (MMs) are very useful tools in achieving this following their use in evaluation of the initial state of a company for planned development journey towards Industry 4.0 (I4.0) readiness and implementation. Study shows that only a limited number of O&G specific roadmaps, MMs, frameworks and readiness assessments are available today. This paper aims to review the currently available Industry 4.0 MMs for manufacturing industries and analyze their applicability in the O&G upstream sector using the systematic literature review (SLR) methodology, recognizing the specific requirements of this industry. The study looks at the key characteristic for O&G sector in relation to the manufacturing sector and identifies research gaps needed to be addressed to successfully support the O&G sector in readiness for Industry 4.0 implementation. An Industry 4.0 maturity model that reflects the industrial realities for the O&G upstream sector more accurately from insights drawn from the reviews of existing MMs is proposed. This reduces the challenges of the transition process towards Industry 4.0 and provides support for the critical change desired for improved efficiency in the sector.


Sign in / Sign up

Export Citation Format

Share Document