Abstract
Zero Defects is one of the ultimate targets for manufacturing quality control and assurance. Such systems are becoming common in advanced manufacturing industries but are at an initial stage in more traditional industrial sectors, such as wood panels, laminates production, pulp and paper processing and composite panels production. This paper proposes the PREFAB framework, applied to the wood based panels industry, to minimize rejected products using AI, machine learning and IoT devices. The framework was built through action research with a Portuguese wood-based panel manufacturing. This framework delivered an innovative decision support system that provides relevant and timely recommendations for shopfloor decision making and to support process/product engineering. Copyright (C) 2021 The Authors.

Abstract
This work addresses the energy-efficient job shop scheduling problem and transport resources with speed scalable machines and vehicles which is a recent extension of the classical job shop problem. In the environment under consideration, the speed with which machines process production operations and the speed with which vehicles transport jobs are also to be decided. Therefore, the scheduler can control both the completion times and the total energy consumption. We propose a mixed-integer linear programming model that can be efficiently solved to optimality for small-sized problem instances.

Abstract
This paper addresses an extension of the flexible job shop scheduling problem by considering that jobs need to be moved around the shop-floor by a set of vehicles. Thus, this problem involves assigning each production operation to one of the alternative machines, finding the sequence of operations for each machine, assigning each transport task to one of the vehicles, and finding the sequence of transport tasks for each vehicle, simultaneously. Transportation is usually neglected in the literature and when considered, an unlimited number of vehicles is, typically, assumed. Here, we propose the first mixed integer linear programming model for this problem and show its efficiency at solving small-sized instances to optimality. In addition, and due to the NP-hard nature of the problem, we propose a local search based heuristic that the computational experiments show to be effective, efficient, and robust.

Abstract
Digital transformation is critical for the competitiveness of SMEs. Digital Innovation Hubs (DIHs) aim to regionally support companies in the development of new products, processes, or services, providing access to advanced technologies. Since DIHs have to be financially sustainable, it is important to discuss which business models are put forward in such complex arrangements. Our main goal is to analyse how DIHs, specialized in Industry 4.0 technologies and services, create, offer, and capture value. The research was conducted through a documentary analysis of reports about DIHs' Business Models, generated by three European initiatives (encompassing more than 300 DIHs). Results demonstrate that one Business Model does not fit all, since regional characteristics, which vary among differentDIH's, are themain drivers to define value creation, offer and capture. This work aims to provide DIH managers insights to help them develop sustainability strategies.

Abstract
This paper focuses on the identification of collaborative strategies and practices adopted by companies of the fashion industry in the management of customized offerings (both products and services) along their supply chain (SC). A multiple case study approach is applied and four companies (both medium and large) were interviewed. The cross-case analysis enabled mapping the cases following two dimensions: type of market asking for the customization (B2B vs. B2C) and scope of customization (products vs. services). The analysis highlights the practices and processes related to the customization, the enabling technologies adopted, and the actors involved by a focal company in the collaboration (both in upstream and downstream networks) to offer the product or service that meet customer needs.

Abstract
AbstractExtreme disruptive events, such as the volcano eruption in Iceland, the Japanese tsunami, and the COVID-19 pandemic, as well as constant changes in customers’ needs and expectations, have forced supply chains to continuously adapt to new environments. Consequently, it is paramount to understand the supply chain characteristics for possible future scenarios, in order to know how to respond to threats and take advantage of the opportunities that the next years will bring. This chapter focuses on describing the characteristics of the supply chain in each of the six macro-scenarios presented in Sardesai et al. (2020b), as final stage of the scenario building methodology. Supply chains for each scenario are characterized in eight dimensions: Products and Services, Supply Chain Paradigm, Sourcing and Distribution, Technology Level, Supply Chain Configuration, Manufacturing Systems, Sales Channel, and Sustainability.