scholarly journals The Key Factors of the Industrial Revolution 4.0 in the Malaysian Smart Manufacturing Context

2022 ◽  
Vol 13 (2) ◽  
pp. 1-19
Author(s):  
Mohd Syaiful Rizal Abd Hamid ◽  
Nor Ratna Masrom ◽  
Nur Athirah Binti Mazlan
Keyword(s):  
Data Exchange ◽  
Manufacturing Industry ◽  
Management Practices ◽  
Industrial Revolution ◽  
Manufacturing Sector ◽  
Current Trend ◽  
Secondary Data ◽  
Primary Data ◽  
Smart Manufacturing ◽  
Key Factors

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.

A Study of Quality Tools and Techniques for Smart Manufacturing in Industry 4.0 in Malaysia

2021 ◽  
pp. 792-816
Author(s):  
Mohd Syaiful Rizal Abd Hamid ◽  
Saifuddin Isa ◽  
Chew Boon Cheong
Keyword(s):  
Management Practices ◽  
Industrial Revolution ◽  
Secondary Data ◽  
Primary Data ◽  
Smart Manufacturing ◽  
Face To Face ◽  
Multiple Case ◽  
Tools And Techniques ◽  
Quality Tools

This chapter explores the key factors for selecting quality tools and techniques in industrial revolution 4.0, particularly in the smart manufacturing context. What are the factors determining which quality tools and techniques are more applicable in specific circumstances related to quality performance in Industrial Revolution 4.0? To answer this question, authors employ a multiple case study and an in-depth literature review as the research design approach. Two key data collection methods (qualitative methods) are used: (1) Primary data from face-to-face interviews with Toyo Memory Technology and Intel Malaysia (2) Secondary data from previous studies. This review, coupled with the case study analysis, leads to the identification of the real implementation of quality tools and techniques in the industries. The chapter can enhance the reader understanding of Industrial Revolution 4.0 and quality management practices as well as highlight opportunities for further research.

A Study of Quality Tools and Techniques for Smart Manufacturing in Industry 4.0 in Malaysia

2020 ◽  
pp. 155-185
Author(s):  
Mohd Syaiful Rizal Abd Hamid ◽  
Saifuddin Isa ◽  
Chew Boon Cheong
Keyword(s):  
Management Practices ◽  
Industrial Revolution ◽  
Secondary Data ◽  
Primary Data ◽  
Smart Manufacturing ◽  
Face To Face ◽  
Multiple Case ◽  
Tools And Techniques ◽  
Quality Tools

This chapter explores the key factors for selecting quality tools and techniques in industrial revolution 4.0, particularly in the smart manufacturing context. What are the factors determining which quality tools and techniques are more applicable in specific circumstances related to quality performance in Industrial Revolution 4.0? To answer this question, authors employ a multiple case study and an in-depth literature review as the research design approach. Two key data collection methods (qualitative methods) are used: (1) Primary data from face-to-face interviews with Toyo Memory Technology and Intel Malaysia (2) Secondary data from previous studies. This review, coupled with the case study analysis, leads to the identification of the real implementation of quality tools and techniques in the industries. The chapter can enhance the reader understanding of Industrial Revolution 4.0 and quality management practices as well as highlight opportunities for further research.

scholarly journals Industry 4.0 : India’s Defence Industry Needs Smart Manufacturing

2019 ◽  
Vol 8 (11S) ◽  
pp. 476-485
Keyword(s):  
Cyber Security ◽  
Production Management ◽  
Industrial Revolution ◽  
Secondary Data ◽  
Current Status ◽  
Primary Data ◽  
Smart Manufacturing ◽  
Sample Population ◽  
Private Industry ◽  
Defence Industry

The Fourth Industrial Revolution (I4.0) envisages fusion of technologies across the physical, digital and biological worlds, and is transforming production, management and governance into a Smart Manufacturing paradigm. It is based on exploitation of current and futuristic technologies such as Internet of Things, 3D Printing (Additive Manufacturing), 5 G connectivity, cyber security, robotics and automation. More than any other industry, defence innovation and manufacturing demand high quality and precision products. This paper brings out the need and current status of India’s defence manufacturing sector (state-controlled Defence Research and Development Organisation(DRDO), Ordnance Factories (OFs), Defence Public Sector Undertakings (DPSUs), and Private Industry including MSMEs) with regard to I4.0, and seeks to establish what needs to be done in adopting features of smart manufacturing, to make it globally competitive. Primary data obtained from a small but knowledgeable sample population, duly analysed with descriptive statistics; followed by secondary data sources, establish the influencing factors. Interpretive Structural Modelling helped formulate a framework for smart manufacturing in India’s defence industry. The paper concludes with recommendations with regard to governmental, and industry stakeholders.

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

2020 ◽  
Author(s):  
Sagil James ◽  
Anupam Shetty
Keyword(s):  
Industry 4.0 ◽  
Industrial Revolution ◽  
Manufacturing Sector ◽  
Implementation Process ◽  
Secondary Data ◽  
Smart Manufacturing ◽  
New Paradigm ◽  
Skill Gaps ◽  
Adoption And Implementation ◽  
The Internet Of Things

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.

scholarly journals Education 4.0: The Effectiveness of VARK Learning Style towards Actualising Industrial Revolution 4.0

2020 ◽  
Vol 10 (3) ◽  
pp. 52
Author(s):  
Shahrul Mizan bin Ismail ◽  
Wan Amir Azlan Wan Haniff
Keyword(s):  
Learning Style ◽  
Data Exchange ◽  
Industrial Revolution ◽  
Current Trend ◽  
Real Life ◽  
Secondary Data ◽  
Cognitive Computing ◽  
Potential Threat ◽  
Scientific Database ◽  
Manufacturing Technologies

While Industrial Revolution 4.0 is a name given to the current trend of automation and data exchange in manufacturing technologies which includes cyber-physical systems, the internet, cloud computing and cognitive computing, Education 4.0 is a response to the needs of it where human and technology are coordinating together to empower new opportunities. This article examines the parties affected by Industrial Revolution 4.0 in relation to preparation needed for them to survive, with reference to Malaysia perspective. Moving forward, this article analyses whether VARK learning style is an appropriate model to measure skills and competencies of learners in an effort to match of what Industrial Revolution 4.0 has to offer. This qualitative research utilizes secondary data gained from scientific database analysis and library research including documents on Industrial Revolution 4.0, Education 4.0 & VARK model. These data were analysed. The study reveals that employees & administrators, generation z as well as educators are relevant learners in the preparation of Industrial Revolution 4.0. Further, VARK learning style is proven ineffective due to imperfect research on such model, combined with the hurdles to implement it in real-life situation and subject to mistakes and oversights in their judgement. This article concludes by stressing the need for policymaker to explore new teaching strategies and evaluate their effectiveness to ensure the learners are prepared to embrace changes and reduce a potential threat of technological unemployment.

scholarly journals DEVELOPMENT OF A QUALITY OUTCOME MATRIX FOR MALAYSIAN SMART MANUFACTURERS

2021 ◽  
Vol 56 (5) ◽  
pp. 601-618
Author(s):  
Nur Athirah Binti Mazlan ◽  
Mohd Syaiful Rizal Abd Hamid ◽  
Nor Ratna Masrom
Keyword(s):  
Case Studies ◽  
Industrial Revolution ◽  
Research Question ◽  
Secondary Data ◽  
Primary Data ◽  
Smart Manufacturing ◽  
Face To Face ◽  
Multiple Case ◽  
Tools And Techniques ◽  
Quality Tools

The objective of this research was to develop a quality outcome matrix by exploring a systematic pattern for selecting quality tools and techniques in the Industrial Revolution 4.0, particularly in the smart manufacturing context. By conducting this analysis, the researchers found homogeneous patterns of sufficient quality case studies that can provide a basis for selecting appropriate groups of quality tools and techniques in different scenarios. Multiple case studies and an in-depth literature review were used as the research design approach. Two qualitative data collection methods were used: (1) primary data from face-to-face interviews with employees at Toyo Memory Technology and Intel Malaysia, and (2) secondary data from a previous study. Our study aimed to answer the following research question: “What are the appropriate tools and techniques concerning circumstances of quality dimensions and smart manufacturing?” Thus, our research developed a diagnostic matrix by developing an outcome matrix for selecting appropriate quality tools and techniques. The scientific novelty of this work is that this is a real-world case study describing the authors’ theoretical and practical prerequisites that can help other researchers and industrial practitioners or manufacturers in selecting the appropriate sets of quality tools and techniques for solving quality problems.

scholarly journals ENTERPRENEURIAL-BASED ENGLISH LEARNING (MISS MAYA) TO BUILD ENTREPRENEURIAL LEADERSHIP FOR STUDENTS COLLEGE

2020 ◽  
Vol 7 (2) ◽  
pp. 37-48
Author(s):  
Eko Heriyanto ◽  
Amin Khudlori
Keyword(s):  
Quantitative Research ◽  
Industrial Revolution ◽  
Current Trend ◽  
Secondary Data ◽  
Primary Data ◽  
English Learning ◽  
Entrepreneurial Leadership ◽  
Cognitive Computing ◽  
Test Analysis ◽  
Intelligent Technology

The industrial revolution is a fusion of automation technology with cyber. The current trend in the industrial world is starting to touch the virtual world with several systems such as cyber physical systems, internet of things (IoT), cloud computing, and cognitive computing. Revolution 4.0 implements intelligent technology that can be connected to various lines of life, including students’ needs. They must be active to form their entrepreneurial leadership to face these challenges. Absolutely, this must be supported by encouragement, collaboration and integration of learning in the field of entrepreneurship. The purposes of this research are to describe the steps of implementing the Miss Maya, to find and describe the advantages of Miss Maya in building a concrete entrepreneurial leadership, and to determine the effectiveness of Miss Maya in English learning. The method used is mix method; qualitative and quantitative research design. Primary data include references/ literature/ journals/ books related to the discussion. Secondary data include documentation and field data of the implementation obtained through observation and interviews. The results of this research are the implementation of Miss Maya can be done through the preparation, implementation and assessment. Through t-test analysis which showed that sig. (2-tailed) of all = 0.000 and the probability less than 0.05, Miss Maya is an effective strategy to be used in English learning. Miss Maya is a futuristic imaginative integrative English learning method with six main elements of doing business which is expected to be able to foster the students’ entrepreneurial leadership to face the industrial revolution 4.0.

Development of Leather Cutting Board from Plastic Waste

2021 ◽  
Vol 116 (12) ◽  
Author(s):  
Fitsum Etefa Ahmed ◽  
Rotick K. Gideon
Keyword(s):  
Manufacturing Industry ◽  
Data Gathering ◽  
Secondary Data ◽  
Melting Process ◽  
Plastic Waste ◽  
Primary Data ◽  
Local Market ◽  
Plastic Recycling ◽  
Reinforcing Material ◽  
The Cost

Cutting is the process in which goods or garment material are cut and converted into pattern shapes of the goods or garment components. There are two methods of Leather cutting, which are hand cutting and machine cutting. Hand cutting is done with the use of hand knife, cutting board and cutting patterns. Machine cutting can be done using semi-automatic cutting machines or fully-automatic cutting machines. Currently, in Ethiopia, different local and foreign investors are participating in leather products manufacturing. Most of the leather product manufacturing industry and some Small and Medium enterprise’s (SME’s) in the country are using leather cutting machines in order to cut leather goods or garment parts. Most of the industry and SMEs are using imported cutting board made of plastics and rubbers. However, these cutting boards are expensive.   This research aimed at developing a cutting board made from HDPE (High-Density Polyethylene) plastic waste as main material, calcium carbonate as a filler and glass fiber as a reinforcing material. Primary and secondary data gathering techniques were applied simultaneously. Primary data were collected through interview and field observation. Secondary data was gathered by reviewing different literature. The cutting board developed through collecting HDPE plastic waste, washing, shredding and melting the shredded plastic with filler and reinforcing material. The melted plastic poured in to cutting board mold and cooled. The developed cutting board was compared with HDPE cutting board available in the local market. The developed board showed relative compression and hardness properties with the HDPE cutting board available in the market. In the cost analysis, the developed cutting board is cheaper than the cutting board which available in the market. However, the cutting board in the market has better surface texture and quality than the developed cutting board. Melting HDPE plastic waste using metal or clay cooking pots and charcoal fire is a tedious task and smoke from the fire will cause human health problem and will affect environment. Consequently, manual plastic melting method is not feasible for mass production, because it is difficult to control the amount of heat (charcoal fire) during melting process. Based on this the authors recommend using machine based plastic melting and molding during HDPE and related plastic recycling.

scholarly journals Sustainable and Smart Manufacturing: An Integrated Approach

2020 ◽  
Vol 12 (6) ◽  
pp. 2280 ◽  
Author(s):  
Mohamed Abubakr ◽  
Adel T. Abbas ◽  
Italo Tomaz ◽  
Mahmoud S. Soliman ◽  
Monis Luqman ◽  
...  
Keyword(s):  
Manufacturing Industry ◽  
Sustainability Assessment ◽  
Negative Impact ◽  
Manufacturing Sector ◽  
Sustainable Manufacturing ◽  
Smart Manufacturing ◽  
Future Research ◽  
Bottom Line ◽  
Manufacturing Performance ◽  
Sustainability Concept

The necessity for decreasing the negative impact of the manufacturing industry has recently increased. This is getting recognized as a global challenge due to the rapid increase in life quality standards, demand, and the decrease in available resources. Thus, manufacturing, as a core of the product provision system and a fundamental pillar of civilized existence, is significantly influenced by sustainability issues. Furthermore, current manufacturing modeling and assessment criteria require intensive revisions and upgrades to keep up with these new challenges. Nearly all current manufacturing models are based on the old paradigm, which was proven to be inadequate. Therefore, manufacturing technology, along with culture and economy, are held responsible for providing new tools and opportunities for building novel resolutions towards a sustainable manufacturing concept. One of such tools is sustainability assessment measures. Revising and updating such tools is a core responsibility of the manufacturing sector to efficiently evaluate and enhance sustainable manufacturing performance. These measures should be adequate to respond to the growing sustainability concerns in pursuit of an integrated sustainability concept. The triple bottom line (TBL) that includes environment, economic, and social dimensions has usually been used to evaluate sustainability. However, there is a lack of standard sets of sustainable manufacturing performance measures. In addition to the sustainability concept, a new concept of smart manufacturing is emerging. The smart manufacturing concept takes advantage of the recent technological leap in Artificial Intelligent (AI), Cloud Computing (CC), and the Internet of Things (IoT). Although this concept offers an important step to boost the current production capabilities to meet the growing need, it is still not clear whether the two concepts of smart manufacturing and sustainability will constructively or destructively interact. Therefore, the current study aims to integrate the sustainable smart manufacturing performance by incorporating sustainable manufacturing measures and discussing current and future challenges that are faced by the manufacturing sector. In addition, the opportunities for future research incorporating sustainable smart manufacturing are also presented.

scholarly journals Factors affecting the performance of Indonesian special food SMEs in entrepreneurial orientation in East Java

2019 ◽  
Vol 13 (2) ◽  
pp. 231-246 ◽  
Author(s):  
Benny Hutahayan
Keyword(s):  
Significant Influence ◽  
Entrepreneurial Orientation ◽  
Business Performance ◽  
Manufacturing Industry ◽  
Secondary Data ◽  
Research Area ◽  
Business Strategies ◽  
Primary Data ◽  
Literature Study ◽  
Content Type

Purpose This study aims to examine comprehensively the factors determining the performance of small and medium enterprises (SMEs) producing Indonesian special food in East Java. Design/methodology/approach This study is quantitative and qualitative. Primary data was collected from entrepreneurs in East Java, those producing Indonesian special food. Secondary data was obtained from the literature, literature study, journals, Central Bureau of Statistics and the office of industry, trade, cooperatives and SMEs in East Java. Areas selected for this study were Surabaya, Madiun, Malang, Pasuruan, Lamongan and Banyuwangi. The population was small and medium entrepreneurs producing Indonesian special food in the selected cities. Based on the PLS sampling rule, the number of samples in each research area was 50, with total of 300 respondents (50 × 6). The methods of collecting primary data were interviews and questionnaire. Data analysis was done using GSCA. Findings The study firstly found the significant influence of entrepreneurial orientation on business strategies of SMEs producing Indonesian special food in East Java. SME managers have a high entrepreneurial orientation. Secondly, it found a significant influence of entrepreneurial orientation on business performance of SMEs producing Indonesian special food in East Java. Thirdly, the study found that government policy is not a moderating variable. Additionally, business strategies have a significant influence on the performance of SMEs producing Indonesian special food in East Java. Finally, dynamics of the environment and business strategy have a significant influence on the performance of manufacturing industry in South Sulawesi. Originality/value To know the effect of entrepreneurial orientation, environmental dynamism, consisting of uncertainty of environment and intensity of competition, and business strategies toward business performance. Considering the findings of the previous studies, the authors would like to re-examine the effect of entrepreneurial orientation on business performance, which also compares the findings of previous studies, especially, the one by Lee and Tsang (2003) on SMEs in Singapore.

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