Technology enablers for the implementation of Industry 4.0 to traditional manufacturing sectors: A review

The traditional manufacturing sectors (footwear, textiles and clothing, furniture and toys, among others) are based on small and medium enterprises with limited capacity on investing in modern production technologies. Although these sectors rely heavily on product customization and short manufacturing cycles, they are still not able to take full advantage of the fourth industrial revolution. Industry 4.0 surfaced to address the current challenges of shorter product life-cycles, highly customized products and stiff global competition. The new manufacturing paradigm supports the development of modular factory structures within a computerized Internet of Things environment. With Industry 4.0, rigid planning and production processes can be revolutionized. However, the computerization of manufacturing has a high degree of complexity and its implementation tends to be expensive, which goes against the reality of SMEs that power the traditional sectors. This paper reviews the main scientific-technological advances that have been developed in recent years in traditional sectors with the aim of facilitating the transition to the new industry standard.This research was supported by the Spanish Research Agency (AEI) and the European Regional Development Fund (ERDF) under the project CloudDriver4Industry TIN2017-89266-R

Scheduling strategies for the furniture industry

Technological developments and more demanding production standards have constantly been pushing the envelope, changing the perception of what is possible and desired in manufacturing processes. Such improvements are often made at marginal cost, yet have the potential to significantly benefit performance, enabling a strong competitive advantage. In this case study, a factory in the furniture industry is considered, where there are vast improvement opportunities and an increase in flexibility is needed. Furthermore, this problem can be best approximated by the flow shop model and the most critical characteristic is sequence-dependent setup times. To address this problem, an iterated greedy with local search meta-heuristic is implemented, which will be responsible for scheduling production orders in the way that best suits makespan and, consequently, productivity. Additionally, OptQuest, the optimiser functionally built into the Flexsim simulating software was also tested against the meta-heuristic and, still through simulation, a local rule was implemented, which allowed each workstation to define its own sequence of jobs, to minimise setup times. Lastly, the best performing of the previous methods was also compared to the original heuristic that had previously been specifically created for this problem. Through testing, it was found that the iterated greedy with local search meta-heuristic was able to generate solutions that had a much better makespan value than the ones produced by OptQuest, while the local rule was not able to provide significant improvement. Then, the meta-heuristic was compared to the original heuristic and, although the newly implemented algorithm did not consider all characteristics of the problem, productivity far outperformed that of the original technique

A Multi Objective Evolutionary Algorithm based on Decomposition for a Flow Shop Scheduling Problem in the Context of Industry 4.0

Under the novel paradigm of Industry 4.0, missing operations have arisen as a result of the increasingly customization of the industrial products in which customers have an extended control over the characteristics of the final products. As a result, this has completely modified the scheduling and planning management of jobs in modern factories. As a contribution in this area, this article presents a multi objective evolutionary approach based on decomposition for efficiently addressing the multi objective flow shop problem with missing operations, a relevant problem in modern industry. Tests performed over a representative set of instances show the competitiveness of the proposed approach when compared with other baseline metaheuristics.Fil: Rossit, Diego Gabriel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Matemática Bahía Blanca. Universidad Nacional del Sur. Departamento de Matemática. Instituto de Matemática Bahía Blanca; Argentina. Universidad Nacional del Sur. Departamento de Ingeniería; ArgentinaFil: Nesmachnow, Sergio. Universidad de la República; UruguayFil: Rossit, Daniel Alejandro. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Matemática Bahía Blanca. Universidad Nacional del Sur. Departamento de Matemática. Instituto de Matemática Bahía Blanca; Argentina. Universidad Nacional del Sur. Departamento de Ingeniería; Argentin

Production Engineering and Management

The annual International Conference on Production Engineering and Management takes place for the sixth time his year, and can therefore be considered a well - established event that is the result of the joint effort of the OWL University of Applied Sciences and the University of Trieste. The conference has been established as an annual meeting under the Double Degree Master Program ‘Production Engineering and Management’ by the two partner universities. The main goal of the conference is to provide an opportunity for students, researchers and professionals from Germany, Italy and abroad, to meet and exchange information, discuss experiences, specific practices and technical solutions used in planning, design and management of production and service systems. In addition, the conference is a platform aimed at presenting research projects, introducing young academics to the tradition of Symposiums and promoting the exchange of ideas between the industry and the academy. Especially the contributions of successful graduates of the Double Degree Master Program ‘Production Engineering and Management’ and those of other postgraduate researchers from several European countries have been enforced. This year’s special focus is on Direct Digital Manufacturing in the context of Industry 4.0, a topic of great interest for the global industry. The concept is spreading, but the actual solutions must be presented in order to highlight the practical benefits to industry and customers. Indeed, as Henning Banthien, Secretary General of the German ‘Plattform Industrie 4.0’ project office, has recently remarked, “Industry 4.0 requires a close alliance amongst the private sector, academia, politics and trade unions” in order to be “translated into practice and be implemented now”. PEM 2016 takes place between September 29 and 30, 2016 at the OWL University of Applied Sciences in Lemgo. The program is defined by the Organizing and Scientific Committees and clustered into scientific sessions covering topics of main interest and importance to the participants of the conference. The scientific sessions deal with technical and engineering issues, as well as management topics, and include contributions by researchers from academia and industry. The extended abstracts and full papers of the contributions underwent a double - blind review process. The 24 accepted presentations are assigned, according to their subject, to one of the following sessions: ‘Direct Digital Manufacturing in the Context of Industry 4.0’, ‘Industrial Engineering and Lean Management’, ‘Management Techniques and Methodologies’, ‘Wood Processing Technologies and Furniture Production’ and ‘Innovation Techniques and Methodologies

Design for additive manufacturing: trends, opportunities, considerations, and constraints

© 2016 CIRP. The past few decades have seen substantial growth in Additive Manufacturing (AM) technologies. However, this growth has mainly been process-driven. The evolution of engineering design to take advantage of the possibilities afforded by AM and to manage the constraints associated with the technology has lagged behind. This paper presents the major opportunities, constraints, and economic considerations for Design for Additive Manufacturing. It explores issues related to design and redesign for direct and indirect AM production. It also highlights key industrial applications, outlines future challenges, and identifies promising directions for research and the exploitation of AM's full potential in industry

Business analytics in industry 4.0: a systematic review

Recently, the term “Industry 4.0” has emerged to characterize several Information Technology and Communication (ICT) adoptions in production processes (e.g., Internet-of-Things, implementation of digital production support information technologies). Business Analytics is often used within the Industry 4.0, thus incorporating its data intelligence (e.g., statistical analysis, predictive modelling, optimization) expert system component. In this paper, we perform a Systematic Literature Review (SLR) on the usage of Business Analytics within the Industry 4.0 concept, covering a selection of 169 papers obtained from six major scientific publication sources from 2010 to March 2020. The selected papers were first classified in three major types, namely, Practical Application, Reviews and Framework Proposal. Then, we analysed with more detail the practical application studies which were further divided into three main categories of the Gartner analytical maturity model, Descriptive Analytics, Predictive Analytics and Prescriptive Analytics. In particular, we characterized the distinct analytics studies in terms of the industry application and data context used, impact (in terms of their Technology Readiness Level) and selected data modelling method. Our SLR analysis provides a mapping of how data-based Industry 4.0 expert systems are currently used, disclosing also research gaps and future research opportunities.The work of P. Cortez was supported by FCT - Fundação para a Ciência e Tecnologia within the R&D Units Project Scope: UIDB/00319/2020. We would like to thank to the three anonymous reviewers for their helpful suggestions

Design for additive manufacturing: Trends, opportunities, considerations, and constraints

The past few decades have seen substantial growth in Additive Manufacturing (AM) technologies. However, this growth has mainly been process-driven. The evolution of engineering design to take advantage of the possibilities afforded by AM and to manage the constraints associated with the technology has lagged behind. This paper presents the major opportunities, constraints, and economic considerations for Design for Additive Manufacturing. It explores issues related to design and redesign for direct and indirect AM production. It also highlights key industrial applications, outlines future challenges, and identifies promising directions for research and the exploitation of AM's full potential in industry

Study and analysis of value stream for Yesco production

This research addresses the application of lean manufacturing concepts to the make-to-order production process sector with a focus on the entertainment sign industry. The goal of this research is to investigate the production: process of Young Electric Sign Company (YESCO) and develop a current state value stream map for different work orders from the time the work order is distributed by the department of layout to the time the finished product is ready to crate. Also, we will analyze production sequences, cycle time, labor time, lead-time and down time for each step of the production process. After the analysis, a more efficient and future state value stream map will be developed by eliminating the non value-added activities and suggestions and recommendations for better manufacturing strategy will be proposed

Effects of distribution planning systems on the cost of delivery in unique make-to-order manufacturing

This thesis investigates the effects of simulation through the use of a distribution planning system (DPS) on distribution costs in the setting of unique make-to-order manufacturers (UMTO). In doing so, the German kitchen furniture industry (GKFI) serves as an example and supplier of primary data. On the basis of a detailed market analysis this thesis will demonstrate that this industry, which mostly works with its own vehicles for transport, is in urgent need of innovative logistics strategies. Within the scope of an investigation into the current practical and theoretical use of DPS, it will become apparent that most known DPS are based on the application of given or set delivery tour constraints. Those constraints are often not questioned in practice and in theory nor even attempted to be omitted, but are accepted in day-to-day operation. This paper applies a different approach. In the context of this research, a practically applied DPS is used supportively for the removal of time window constraints (TWC) in UMTO delivery. The same DPS is used in ceteris paribus condition for the re-routing of deliveries and hereby supports the findings regarding the costliness of TWC. From this experiment emerges an overall cost saving of 50.9% and a 43.5% reduction of kilometres travelled. The applied experimental research methodology and the significance of the resulting savings deliver the opportunity to analyse the removal of delivery time window restrictions as one of many constraints in distribution logistics. The economic results of this thesis may become the basis of discussion for further research based on the applied methodology. From a practical point of view, the contributions to new knowledge are the cost savings versus the change of demand for the setting of TWC between the receiver of goods and the UMTO supplier. On the side of theoretical knowledge, this thesis contributes to filling the gap on the production – distribution problem from a UMTO perspective. Further contributions to knowledge are delivered through the experimental methodology with the application of a DPS for research in logistics simulation