New Tasks in Old Jobs: Drivers of Change and Implications for Job Quality

This overview report summarises the findings of 20 case studies looking at recent changes in the task content of five manufacturing occupations (car assemblers, meat processing workers, hand-packers, chemical products plant and machine operators and inspection engineers) as a result of factors such as digital transformations, globalisation and offshoring, increasing demand for high quality standards and sustainability. It also discusses some implications in terms of job quality and working life. The study reveals that the importance of physical tasks in manufacturing is generally declining due to automation; that more intensive use of digitally controlled equipment, together with increasing importance of quality standards, involve instead a growing amount of intellectual tasks for manual industrial workers; and that the amount of routine task content is still high in the four manual occupations studied. Overall, the report highlights how qualitative contextual information can complement existing quantitative data, offering a richer understanding of changes in the content and nature of jobs

Robotics and automated systems in construction: Understanding industry-specific challenges for adoption

© 2019 The Authors The construction industry is a major economic sector, but it is plagued with inefficiencies and low productivity. Robotics and automated systems have the potential to address these shortcomings; however, the level of adoption in the construction industry is very low. This paper presents an investigation into the industry-specific factors that limit the adoption in the construction industry. A mixed research method was employed combining literature review, qualitative and quantitative data collection and analysis. Three focus groups with 28 experts and an online questionnaire were conducted. Principal component and correlation analyses were conducted to group the identified factors and find hidden correlations. The main identified challenges were grouped into four categories and ranked in order of importance: contractor-side economic factors, client-side economic factors, technical and work-culture factors, and weak business case factors. No strong correlation was found among factors. This study will help stakeholders to understand the main industry-specific factors limiting the adoption of robotics and automated systems in the construction industry. The presented findings will support stakeholders to devise mitigation strategies

The impact of industry 4.0 on supply chains

The Fourth Industrial Revolution, known as Industry 4.0 (I4.0), is fundamentally changing the way businesses operate from product development to sales. Yet, research usually focuses on its impact on production or logistics alone and little research has been done on how the supply chains (SC) of the future will look like. In this work project, an analysis of the impact of I4.0 on SC was developed from the review of published literature, with the inclusion of small case studies that served as concrete examples of this impact. From this, a vision for the future of SC was developed

Smart Technology in Construction Industry: Opportunity during COVID-19 Pandemic

The construction industry is a sector that plays an essential role in economic growth. The COVID-19 pandemic is an uncertain situation that significantly affects humans and industries, including the construction industry. The operational construction projects are complex with various activities and involve a large of workers. Prevention of the spread of COVID-19 that changes lifestyles and improves technology adoption. This study examines the relationship between increased technology adoption and limited workers’ social interaction in construction projects during the pandemic. A questionnaire survey was conducted to construction workers in DKI Jakarta, 74 valid responses were collected and correlation analyses were performed with SPSS version 28. The result of this study indicated a significant and positive correlation between increased technology adoption and limited workers’ social interaction in a construction project during the pandemic. There are opportunities for the construction industry to implement a digital transformation, Building Information Modelling (BIM), and intelligence visualization technologies to cope with the impact of the COVID-19 pandemic on construction activities. This study provides evidence that smart technologies application has a significant role in supporting the construction industry to mitigate the impact of the COVID-19 pandemic and opportunities for continuous improvement towards post-pandemic

Smart Industry - Better Management

The ebook edition of this title is Open Access and freely available to read online. Smart industry requires better management. As industrial and production systems are future-proofed, becoming smart and interconnected through use of new manufacturing and product technologies, work is advancing on improving product needs, volume, timing, resource efficiency, and cost, optimally using supply chains. Presenting innovative, evidence-based, and cutting-edge case studies, with new conceptualizations and viewpoints on management, Smart Industry, Better Management explores concepts in product systems, use of cyber physical systems, digitization, interconnectivity, and new manufacturing and product technologies. Contributions to this volume highlight the high degree of flexibility in people management, production, including product needs, volume, timing, resource efficiency and cost in being able to finely adjust to customer needs and make full use of supply chains for value creation. Smart Industry, Better Management illustrates how industry can enabled by a more network-centric approach, making use of the value of information and the latest available proven manufacturing techniques

Conceptual Key Competency Model for Smart Factories in Production Processes

AbstractBackground and Purpose: The aim of the study is to develop a conceptual key competency model for smart factories in production processes, focused on the automotive industry, as innovation and continuous development in this industry are at the forefront and represent the key to its long-term success.Methodology: For the purpose of the research, we used a semi-structured interview as a method of data collection. Participants were segmented into three homogeneous groups, which are industry experts, university professors and secondary education teachers, and government experts. In order to analyse the qualitative data, we used the method of content analysis.Results: Based on the analysis of the data collected by structured interviews, we identified the key competencies that workers in smart factories in the automotive industry will need. The key competencies are technical skills, ICT skills, innovation and creativity, openness to learning, ability to accept and adapt to change, and various soft skills.Conclusion: Our research provides insights for managers working in organisations that are transformed by Industry 4.0. For instance, human resource managers can use our results to study what competencies potential candidates need to perform well on the job, particularly in regards to planning future job profiles in regards related to production processes. Moreover, they can design competency models in a way that is coherent with the trends of Industry 4.0. Educational policy makers should design curricula that develop mentioned competencies. In the future, the results presented here can be compared and contrasted with findings obtained by applying other empirical methods