Search results

The purpose of this paper is to investigate how different manufacturing technologies are bundled together and how these bundles influence operations performance and, indirectly, business performance. With the emergence of Industry 4.0 (I4.0) technologies, manufacturing companies can use a wide variety of advanced manufacturing technologies (AMT) to build an efficient and effective production system. Nevertheless, the literature offers little guidance on how these technologies, including novel I4.0 technologies, should be combined in practice and how these combinations might have a different impact on performance.

Using a survey study of 165 manufacturing plants from 11 different countries, we use factor analysis to empirically derive three distinct manufacturing technology bundles and structural equation modeling to quantify their relationship with operations and business performance.

Our findings support an evolutionary rather than a revolutionary perspective. I4.0 technologies build on traditional manufacturing technologies and do not constitute a separate direction that would point towards a fundamental digital transformation of companies within our sample. Performance effects are rather weak: out of the three technology bundles identified, only “automation and robotization” have a positive influence on cost efficiency, while “base technologies” and “data-enabled technologies” do not offer a competitive advantage, neither in terms of cost nor in terms of differentiation. Furthermore, while the business performance impact is positive, it is quite weak, suggesting that financial returns on technology investments might require longer time periods.

Relying on a complementarity approach, our research offers a novel perspective on technology implementation in the I4.0 era by investigating novel and traditional manufacturing technologies together.

The use of technology in 4th industrial revolution is at its peak. Industries are trying to reduce the consumption of resources by effectively utilizing information and technology to connect different functioning agents of the manufacturing industry. Without digitization “Industry 4.0” will be a virtual reality. The present survey-based study explores the factual status of digital manufacturing in the Northern India.

After an extensive literature review, a questionnaire was designed to gather different viewpoints of Indian industrial practitioners. The first half contains questions related to north Indian demographic factors which may affect digitalization of India. The latter half includes the queries concerned with various operational factors (or drivers) driving the digital revolution without ignoring Indian constraints.

The focus of this survey was to understand the current level of digital revolution under the ongoing push by the Indian government focused upon digital movement. The analysis included non-parametric testing of the various demographic and functional factors impacting the digital echoes, specifically in Northern India. Findings such as technological upgradations were independent of type of industry, the turnover or the location. About 10 key operational factors were thoughtfully grouped into three major categories—internal Research and Development (R&D), the capability of the supply chain and the capacity to adapt to the market. These factors were then examined to understand how they contribute to digital manufacturing, utilizing an appropriate ordinal logistic regression. The resulting predictive analysis provides seldom-seen insights and valuable suggestions for the most effective deployment of digitalization in Indian industries.

The country-specific Industry 4.0 literature is quite limited. The survey mainly focuses on the National Capital Region. The number of demographic and functional factors can further be incorporated. Moreover, an addition of factors related to ecology, environment and society can make the study more insightful.

The present work provides valuable insights about the current status of digitization and expects to facilitate public or private policymakers to implement digital technologies in India with less efforts and the least resistance. It empowers India towards Industry 4.0 based tools and techniques and creates new socio-economic dimensions for the sustainable development.

The quantitative nature of the study and its statistical predictions (data-based) are novel. The clubbing of similar success factors to avoid inter-collinearity and complexity is seldom seen. The predictive analytics provided in this study is quite elusive as it provides directions with logic. It will help the Indian Government and industrial strategists to plan and perform their interventions accordingly.

One of the most hyped concepts in the manufacturing industry is ‘Industry 4.0’. The ‘Industry 4.0’ concept is grabbing the attention of every manufacturing industry across the globe because of its immense applications. This phenomenon is an advanced version of Industry 3.0, combining manufacturing processes and the latest Internet of Things (IoT) technologies. The main advantage of this paradigm shift is efficiency and efficacy in the manufacturing process with the help of advanced automated technologies. The concept of ‘Industry 4.0’ is contemporary, so it falls under exploratory study. Therefore, the research methodology is thematic narration grounded on secondary data (online) analysis. In this light, this chapter aims to explain ‘Industry 4.0’ in terms of concepts, theories and models based on the Web of Science (WoS) database. The data include research manuscripts, book chapters, blogs, white papers, news items and proceedings. The study details the latest technologies behind the ‘Industry 4.0’ phenomenon, different business intelligence technologies and their practical implications in some manufacturing industries. This chapter mainly elaborates on Industry 4.0 frameworks designed by (1) PwC (2) IBM (3) Frost & Sullivan.

This paper examines the relationship between different manufacturing strategies and Industry 4.0's (I4.0) critical success factors (CSFs) and technology adoption.

For that, the authors surveyed 165 practitioners from different manufacturers. Participants provided information about the levels of product customization and production volume in their companies. They also indicated the adoption level of I4.0 technologies and CSFs. Using multivariate data techniques, the authors identified four clusters of different manufacturing strategies and two readiness levels based on the establishment of I4.0 CSFs. The adoption level of I4.0 technologies was then cross compared among clusters to identify which technologies are more likely to be supported.

The findings indicate that, in low-readiness companies, the adoption level of I4.0 technologies does not significantly differ between manufacturing strategies. However, when companies present a higher I4.0 readiness, the adoption of I4.0 technologies seem to vary according to the existing manufacturing strategy.

This study sheds light on the influence that manufacturing strategies may have on the digital transformation of companies, highlighting which strategies are more likely to offer a context to successfully adopt I4.0 technologies. The identification of these relationships helps to define the expectation regarding the company's digital transformation, determining coherent benchmarks and allowing managers to anticipate potential issues.

The role of industry 4.0 (I4.0) technologies for organizations to achieve a competitive advantage and mitigate disruptive emergency situations are well exhibited in literature. However, more light needs to be thrown into implementing I4.0 technologies to digitally transform organizations. This paper introduces a novel framework for formulating manufacturing strategy 4.0 (MS 4.0) that guides organizations to implement I4.0 successfully.

The experts working in I4.0 and technology management domains were interviewed to determine the definition, role and process for formulating MS 4.0. Text mining using VOSViewer© is performed on the experts' opinions to determine the key terms from the opinions through keyword analysis. The identified key terms are mapped together using the existing traditional manufacturing strategy formulation framework to develop the MS 4.0 framework. Finally, the proposed MS 4.0 framework is validated through a triangulation approach.

This study captured the role, definition and process to formulate MS 4.0 and proposed a framework to help practitioners implement I4.0 at manufacturing organizations to achieve competitiveness during normal and emergency situations.

The proposed MS 4.0 framework can assist industry practitioners in formulating the strategy for implementing the I4.0 technology/gies to digitally transform their manufacturing firm to retain the maximum manufacturing output and become market competent in normal and emergency situations.

This study is the first of its kind in the body of knowledge to formulate a digital transformation strategy, i.e. MS 4.0, to implement I4.0 technologies through a manufacturing strategic lens.

Changing manufacturing policy and manufacturing technology has had serious implications for production managers. A survey to identify the nature and extent of the impact of changes in manufacturing technology on the jobs of production or manufacturing managers shows that managers are concerned about the changing nature of their jobs and are increasingly dissatisfied with their roles. Their jobs are diminished but more stressful because they must maintain responsibility over a system over which they have little control. Yet they need a wider range of skills, e.g. people management and a broad knowledge of different subjects, to perform this role. The inevitability of change and the future directions in this area are discussed.

This paper empirically investigates the processes by which manufacturing firms create radical innovations in their core production process, referred to as radical manufacturing technology innovations (RMTI). The purpose of this paper is to improve the understanding of the processes and practices manufacturing firms use to create RMTI.

Creation processes for 23 RMTI projects from diverse industry and technology contexts are explored. Data were collected via semi-structured interviews, and an inductive analysis was carried out to identify similarities and differences in RMTI types and creation processes.

Three types of RMTI and three alternative RMTI creation processes are revealed and characterized. An integrated view is developed of the activities of the equipment supplier and the manufacturing firm, highlighting their different roles and interaction across the three RMTI creation process types.

The exploratory design limits the depth of the analysis per RMTI project, and the focus is on manufacturing technology innovations in one country. The results extend previous case and context-specific findings on RMTI creation processes and provide novel frameworks for cross-case comparisons.

The manufacturing firms’ proactive role in RMTI creation is defined. A framework is proposed for using different RMTI creation processes for different types of RMTI.

This study addresses recent calls for empirical research on understanding the ways in which process innovations unfold in manufacturing firms. The findings emphasize the role of manufacturing firms as creators of RMTI in addition to their role as innovation adopters and implementers and reveal the suitability of different RMTI creation processes for different RMTI types.

Addresses the relationship between firm performance on 15 manufacturing attributes and the extensiveness of advanced manufacturing technology (AMT) portfolios that firms adopt. Mail survey data obtained from 116 manufacturing firms in the USA that had adopted a variety of AMT are used in this research. On average, responding firms reported some improvements in manufacturing performance for all variables except changes in average labour cost (total labour cost/number of direct and indirect labour employees). Adoption of AMT tended to result in marginal reductions in the number of operators and marginal increases in average labour costs across all technology portfolio classifications. For all technology groups, firms recorded their highest level of improvement for product quality, and operator output rates/operator productivity. The majority of firms that had adopted both integrated process technologies and integrated information/logistic technologies reported improvements for 14 of the 15 performance attributes covered in this study.

This paper has two objectives: first, to investigate the state-of-the-art of Industry 4.0 (I4.0) adoption in Italian manufacturing firms and, second, to understand variations in technologies implemented and business functions involved, benefits perceived, and obstacles encountered in I4.0 implementation over a three-year period.

The approach adopted in this research is descriptive, nesting longitudinal features. The paper presents a descriptive survey of 102 Italian manufacturing companies. The authors also evaluated non-response biases. The longitudinal approach was achieved by comparing the responses of the 40 sub-samples in common with a second similar survey launched three years prior, which aimed to identify patterns of evolution in the adoption of the I4.0 paradigm.

Survey findings demonstrate that Italian manufacturing companies still have limited awareness of I4.0 technologies, and the adoption of I4.0 technologies differs per technology. Company size and information system coverage level are the two factors that impact the company's technology adoption level. The comparative study shows that knowledge and adoption increase in a three-year interval with an unbalanced involvement of business functions regarding the I4.0 transformation. Indeed, companies are still seeking I4.0 solutions to reduce costs and lead times primarily, and the benefits perceived by companies are shown to be related to the number of I4.0 technologies in use. Finally, when companies put the I4.0 technologies into practice, competence is constantly considered the most significant barrier.

This paper aims at conducting a thorough investigation into the development of I4.0 adoption in manufacturing companies. The main limitation of this study concerns the limited number of subjects involved in the longitudinal study (40) and the focus on a limited geographical area (Italy). In addition, more I4.0 technologies could also be incorporated into the survey protocol to gain further insight into I4.0 development.

The authors provide one of the first attempts to assess the variations of I4.0 implementation concerning technology adoption, business function involvement, and the alteration of benefits and obstacles. Several studies presented in the literature highlight the lack of longitudinal studies investigating the development of the I4.0 paradigm in a specific manufacturing context: this paper is the attempt at filling this gap.

Examines the tenth published year of the ITCRR. Runs the whole gamut of textile innovation, research and testing, some of which investigates hitherto untouched aspects. Subjects discussed include cotton fabric processing, asbestos substitutes, textile adjuncts to cardiovascular surgery, wet textile processes, hand evaluation, nanotechnology, thermoplastic composites, robotic ironing, protective clothing (agricultural and industrial), ecological aspects of fibre properties – to name but a few! There would appear to be no limit to the future potential for textile applications.