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Cloud Manufacturing (CM) is the manufacturing version of Cloud Computing and aims to increase flexibility in the provision of manufacturing services. On-demand manufacturing services can be requested by users to the cloud and this enables the concept of Manufacturing-as-a-Service (MaaS). Given the considerable number of prototypes and proofs of concept addressed in literature, this work seeks real CM platforms to study them from a business perspective, in order to discover what MaaS concretely means today and how these platforms are operating.

Since the number of real applications of this paradigm is very limited (if the authors exclude prototypes), the research approach is qualitative. The paper presents a multiple-case analysis of 6 different platforms operating in the manufacturing field today. It is based on empirical data and inductively researches differences among them (e.g. stakeholders, operational flows, capabilities offered and scalability level).

MaaS has come true in some contexts, and today it is following two different deployment models: open or closed to the provider side. The open architecture is inspired by a truly open platform which allows any company to be part of the pool of service providers, while the closed architecture is limited to a single service provider of the manufacturing services, as it happens in most cloud computing services.

The research shoots a picture of what MaaS offers today in term of capabilities, what are the deployment models and finally suggests a framework to assess different levels of development of MaaS platforms.

This paper presents approaches to determine a network-based pricing for 3D printing services in the context of a two-sided manufacturing-as-a-service marketplace. The purpose of this study is to provide cost analytics to enable service bureaus to better compete in the market by moving away from setting ad hoc and subjective prices.

A data mining approach with machine learning methods is used to estimate a price range based on the profile characteristics of 3D printing service suppliers. The model considers factors such as supplier experience, supplier capabilities, customer reviews and ratings from past orders and scale of operations, among others, to estimate a price range for suppliers’ services. Data were gathered from existing marketplace websites, which were then used to train and test the model.

The model demonstrates an accuracy of 65 per cent for US-based suppliers and 59 per cent for Europe-based suppliers to classify a supplier’s 3D printer listing in one of the seven price categories. The improvement over baseline accuracy of 25 per cent demonstrates that machine learning-based methods are promising for network-based pricing in manufacturing marketplaces

Conventional methodologies for pricing services through activity-based costing are inefficient in strategically priced 3-D printing service offering in a connected marketplace. As opposed to arbitrarily determining prices, this work proposes an approach to determine prices through data mining methods to estimate competitive prices. Such tools can be built into online marketplaces to help independent service bureaus to determine service price rates.

The purpose of this paper is to identify and classify the available types of 3D printing services, with the scope of determining the potential implications that such services could have on the supply chains of manufacturing firms and creating a research agenda for future studies.

The authors review the current literature on the potential supply chain impacts of 3D printing and evaluate the 3D printing services provided by 404 firms in selected European markets.

The results show that 3D printing services form a rapidly evolving industry, with new service providers entering the market on a regular basis. Evidence from the European markets investigated suggests that services can be classified into three distinct categories: generative, facilitative and selective services.

This paper represents an attempt to take stock of a fast-moving and potentially paradigm-shifting market. The implications are dynamic as new applications, business models and techniques are continually being developed. Further studies are required to substantiate the findings.

Three categories of 3D printing services that could significantly impact supply chain configurations of the future are proposed. Several issues specific to 3D printing services raised in the research agenda require further scrutiny and substantiation before services can reach their full potential.

This paper provides an overview of the growing 3D printing services industry, highlighting how the market might change as additive manufacturing technology matures.

The purpose of this paper is to conduct a state-of-the-art review of the ongoing research on the Industry 4.0 phenomenon, highlight its key design principles and technology trends, identify its architectural design and offer a strategic roadmap that can serve manufacturers as a simple guide for the process of Industry 4.0 transition.

The study performs a systematic and content-centric review of literature based on a six-stage approach to identify key design principles and technology trends of Industry 4.0. The study further benefits from a comprehensive content analysis of the 178 documents identified, both manually and via IBM Watson’s natural language processing for advanced text analysis.

Industry 4.0 is an integrative system of value creation that is comprised of 12 design principles and 14 technology trends. Industry 4.0 is no longer a hype and manufacturers need to get on board sooner rather than later.

The strategic roadmap presented in this study can serve academicians and practitioners as a stepping stone for development of a detailed strategic roadmap for successful transition from traditional manufacturing into the Industry 4.0. However, there is no one-size-fits-all strategy that suits all businesses or industries, meaning that the Industry 4.0 roadmap for each company is idiosyncratic, and should be devised based on company’s core competencies, motivations, capabilities, intent, goals, priorities and budgets.

The first step for transitioning into the Industry 4.0 is the development of a comprehensive strategic roadmap that carefully identifies and plans every single step a manufacturing company needs to take, as well as the timeline, and the costs and benefits associated with each step. The strategic roadmap presented in this study can offer as a holistic view of common steps that manufacturers need to undertake in their transition toward the Industry 4.0.

The study is among the first to identify, cluster and describe design principles and technology trends that are building blocks of the Industry 4.0. The strategic roadmap for Industry 4.0 transition presented in this study is expected to assist contemporary manufacturers to understand what implementing the Industry 4.0 really requires of them and what challenges they might face during the transition process.

The purpose of this paper is to review and explore the evolution, advances and future trends of cloud manufacturing, placing the focus on the quality of services. Moreover, moving toward the new trend of cyber-physical systems (CPS), a cloud-based cyber-physical system (CBCPS) is proposed combining the key enabling techniques of this decade, namely Internet of Things (IoT), cloud computing, Big Data analytics and CPS.

First, an extensive review is made on cloud computing and its applications in manufacturing sectors, namely product development, manufacturing processes and manufacturing systems management. Second, a conceptual CBCPS which combines key enabling techniques including cloud computing, CPS and IoT is proposed. Finally, a review on the quality of the services (QoS) presented in the second step, along with the main security issues of cloud manufacturing, is conducted.

The findings of this review indicate that the combination of the key enabling techniques presented in the CBCPS will lead to a new manufacturing paradigm capable of facing the new challenges and trends. The opportunities, as well as the challenges and barriers of the proposed framework are presented, concluding that the transition into this whole new era of networked computing and manufacturing has a valuable impact, but also generates several security and quality issues.

The paper is the first to specifically study the QoS as a factor in the proposed manufacturing paradigm.

Time is a resource that all companies have. Using it to compete in the global market is now an essential strategy.

The emergence the fourth industrial revolution, known as well as industry 4.0, and its applications in the manufacturing sector ushered a new era for the business entities. It not only promises enhancement in operational efficiency but also magnify sustainable operations practices. This current paper provides a thorough bibliometric and network analysis of more than 600 articles highlighting the benefits in favor of the sustainability dimension in the industry 4.0 paradigm.

The analysis begins by identifying over 1,000 published articles in Scopus, which were then refined to works of proven influence and those authored by influential researchers. Using rigorous bibliometric software, established and emergent research clusters were identified for intellectual network analysis, identification of key research topics, interrelations and collaboration patterns.

This bibliometric analysis of the field helps graphically to illustrate the publications evolution over time and identify areas of current research interests and potential directions for future research. The findings provide a robust roadmap for mapping the research territory in the field of industry 4.0 and sustainability.

As the literature on sustainability and industry 4.0 expands, reviews capable of systematizing the main trends and topics of this research field are relevant.

The purposes of this research article are as follows: to explore the understanding of the Industry 4.0 (I4.0) concept among Indian manufacturing industries, to determine the motivating factors for I4.0 implementation, to identify I4.0 enabling technologies which are used by Indian manufacturing industries and assess their sustainability, to explore the impact of above identified enabling technologies on sustainability pillars, to determine how Indian manufacturing industries interpret the concept of I4.0 and to develop a road map for I4.0 implementation and sustainability.

To perform this research work, a dual research methodology was adopted. Questionnaires were sent to 16 Indian manufacturing industries, and expert interviews were conducted with seven experts who have been practicing the I4.0 concept since the last three years in their business. Also, a sustainability measurement tool was developed to measure the sustainability of the used I4.0 enabling technologies.

In this research article, it is found that smart sensors and robot arms have high sustainability, whereas cyber physical systems (CPSs) and big data analytics have low sustainability. During an expert interview, it has been found that adoption of the I4.0 concept in Indian manufacturing industries is creating job loss fear in employees. Also, it is found that Indian workers must be trained to adopt and sustain I4.0 enabling technologies.

The sustainability of I4.0 enabling technologies in Indian manufacturing industries was indicated by analyzing responses received through questionnaires and expert interviews. There are other measures of sustainability which are beyond this study. Further studies are expected to fill the gap.

The authors have explored reasons for low sustainability of I4.0 enabling technologies in Indian manufacturing industries, suggested a road map for its implementation and sustainability and identified the relationship between different parameters (such as job loss, job creation, workers’ qualification and business profit) and I4.0 sustainability, therefore helping Indian organizations to develop sustainable manufacturing systems based on the I4.0 concept.

This research article gives an idea about sustainability of I4.0 enabling technologies in Indian manufacturing industries.

This study aims to identify the critical factors (barriers and drivers) influencing the adoption of cloud computing (ACC) in the manufacturing sector in India.

In this study, a mixed methodology approach is used. Interviews are conducted to investigate factors (drivers and barriers) influencing the ACC, which are further categorized as controllable determinants (weaknesses and strengths) and uncontrollable determinants (threats and opportunities) using a SWOT analysis. Fuzzy analytic hierarchy process (FAHP) has been utilized to highlight the most critical drivers as well as barriers. Finally, decision-making trial and evaluation laboratory (DEMATEL) has been used to find the cause-effect relationships among factors and their influence on the decision of adoption.

The manufacturing sector is in the digital and value change transformation phase with Industry 4.0, that is, the next industrial revolution. The 24 critical factors influencing ACC are subdivided into strengths, weaknesses, opportunities and threats. The FAHP analysis ranked time to market, competitive advantage, business agility, data confidentiality and lack of government policy standards as the most critical factors. The cause-effect relationships highlight that time to market is the most significant causal factor, and resistance to technology is the least significant effect factor. The results of the study elucidate that the strengths of ACC are appreciably more than its weaknesses.

This study couples the technology acceptance model (TAM) with technology-organization-environment (TOE) framework and adds an economic perspective to examine the significant influences of ACC in the Indian manufacturing sector. Further, it contributes to the knowledge of ACC in general and provides valuable insights into interrelationships among factors influencing the decision and strategies of adoption in particular.

This is the first scholarly work in the Indian manufacturing sector that uses the analysis from SWOT and FAHP approach as a base for identifying cause-effect relationships between the critical factors influencing ACC. Further, based on the extant literature and analysis of this work, an adoption framework has been proposed that justifies that ACC is not just a technological challenge but is also an environmental, economic and organizational challenge that includes organizational issues, costs and need for adequate government policies.