Survey on Additive Manufacturing, Cloud 3D Printing and Services

Cloud Manufacturing (CM) is the concept of using manufacturing resources in a service oriented way over the Internet. Recent developments in Additive Manufacturing (AM) are making it possible to utilise resources ad-hoc as replacement for traditional manufacturing resources in case of spontaneous problems in the established manufacturing processes. In order to be of use in these scenarios the AM resources must adhere to a strict principle of transparency and service composition in adherence to the Cloud Computing (CC) paradigm. With this review we provide an overview over CM, AM and relevant domains as well as present the historical development of scientific research in these fields, starting from 2002. Part of this work is also a meta-review on the domain to further detail its development and structure

Products and Services

Today’s global economy offers more opportunities, but is also more complex and competitive than ever before. This fact leads to a wide range of research activity in different fields of interest, especially in the so-called high-tech sectors. This book is a result of widespread research and development activity from many researchers worldwide, covering the aspects of development activities in general, as well as various aspects of the practical application of knowledge

Strategies to Mitigate Supply Chain Disruptions in Grocery Businesses

Supply chains have become more complex in the global economy, which has made supply chain disruptions inevitable. Disruptions can cause loss of profitability and hinder business growth. The goal of this multiple case study was to explore strategies to mitigate the effects of disruption in grocery store supply chains. The conceptual framework for this study was the resource dependency theory, which stipulates that firms rely on other businesses in the external environment for critical resources to create a competitive edge. Four purposively selected participants from 4 grocery store businesses in Northwest Arkansas participated in semistructured interviews and provided organizational documentation for this study. The participants were supply chain managers who had knowledge about disruptions and had successfully mitigated disruptions in their grocery stores\u27 supply chains. Yin\u27s 5-step process was used to analyze data, which involved compiling the database, disassembling data, reassembling data, interpreting data, and making a conclusion. Four themes emerged from the data analysis: supply chain partners\u27 collaboration, multiple supply base and supplier qualification, inventory management, and information technology and communication. The uninterrupted flow of grocery merchandise to the community could result in a positive social change by helping to ensure that community members have timely access to food

Sustainable Industrial Engineering along Product-Service Life Cycle/Supply Chain

Sustainable industrial engineering addresses the sustainability issue from economic, environmental, and social points of view. Its application fields are the whole value chain and lifecycle of products/services, from the development to the end-of-life stages. This book aims to address many of the challenges faced by industrial organizations and supply chains to become more sustainable through reinventing their processes and practices, by continuously incorporating sustainability guidelines and practices in their decisions, such as circular economy, collaboration with suppliers and customers, using information technologies and systems, tracking their products’ life-cycle, using optimization methods to reduce resource use, and to apply new management paradigms to help mitigate many of the wastes that exist across organizations and supply chains. This book will be of interest to the fast-growing body of academics studying and researching sustainability, as well as to industry managers involved in sustainability management

Supply chain outsourcing risk using an integrated stochastic-fuzzy optimization approach.

a b s t r a c t A stochastic fuzzy multi-objective programming model is developed for supply chain outsourcing risk management in presence of both random uncertainty and fuzzy uncertainty. Utility theory is proposed to treat stochastic data and fuzzy set theory is used to handle fuzzy data. An algorithm is designed to solve the proposed integrated model. The new model is solved using the proposed algorithm for a three stage supply chain example. Computation suggests an analysis of risk averse and procurement behavior, which indicates that a more risk-averse customer prefers to order less under uncertainty and risk. Tradeoff game analysis yields supported points on the trade-off curve, which can help decision makers to identify proper weighting scheme where Pareto optimum is achieved to select preferred suppliers