The impacts of Industry 4.0 enabling technologies on operational strategy

Purpose: Adapting to technological advances is a pertinent challenge for operations in the Manaus Industrial Park. This study aims to address the following research question: how do Industry 4.0 (I4.0) enabling technologies impact the quality and flexibility strategy in the Manaus Industrial Park? Originality / Value: This study developed a systematic and structured way to understand the benefits of I4.0 technologies in quality strategies and flexibility of manufacturing production lines. Manaus Industrial Park plays an essential role in the development of innovations in the Amazon region, and companies must be competitive in this new context of digitization of manufacturing. Methods: This study used a qualitative and descriptive approach. Data were collected through semi-structured interviews with industrial managers from 12 companies that operate in the Manaus Industrial Park. Results: The results of this work point to a frequent use of computer systems to integrate machines in operations, such as the use of M2M technology and cyber-physical systems. The companies researched in the Manaus Industrial Park are adopting essential technologies to create the infrastructure for the I4.0 implantation. This is the first step to making smart factories in the future. Conclusions: Industry 4.0 enabling technologies affect operations' quality and flexibility strategy, promoting cost savings by optimizing production processes

“China Manufacturing 2025” Challenges and Opportunities for Small and Medium Chinese Businesses

Rising labor costs and shifting consumer demands are causing Hangzhou manufacturers to reevaluate their current manufacturing practices. As part of China’s push for internalization of automation, Greentech Investments wants to invest in the development of Chinese manufacturing. We explored automation implementation methods and workforce changes using surveying, interviewing, and field studies of manufacturers to assess current transition obstacles. We found that unskilled labor shortages are limiting manufacturing growth and developed a guide for industry automation adoption to combat this deficiency

Optimal Planning Modulo Theories

Planning for real-world applications requires algorithms and tools with the ability to handle the complexity such scenarios entail. However, meeting the needs of such applications poses substantial challenges, both representational and algorithmic. On the one hand, expressive languages are needed to build faithful models. On the other hand, efficient solving techniques that can support these languages need to be devised. A response to this challenge is underway, and the past few years witnessed a community effort towards more expressive languages, including decidable fragments of first-order theories. In this work we focus on planning with arithmetic theories and propose Optimal Planning Modulo Theories, a framework that attempts to provide efficient means of dealing with such problems. Leveraging generic Optimization Modulo Theories (OMT) solvers, we first present domain-specific encodings for optimal planning in complex logistic domains. We then present a more general, domain- independent formulation that allows to extend OMT planning to a broader class of well-studied numeric problems in planning. To the best of our knowledge, this is the first time OMT procedures are employed in domain-independent planning

Towards an infrastructure for preparation and control of intelligent automation systems

In an attempt to handle some of the challenges of modern production, intelligent automation systems offer solutions that are flexible, adaptive, and collaborative. Contrary to traditional solutions, intelligent automation systems emerged just recently and thus lack the supporting tools and infrastructure that traditional systems nowadays take for granted. To support efficient development, commissioning, and control of such systems, this thesis summarizes various lessons learned during years of implementation. Based on what was learned, this thesis investigates key features of infrastructure for modern and flexible intelligent automation systems, as well as a number of important design solutions. For example, an important question is raised whether to decentralize the global state or to give complete access to the main controller.Moreover, in order to develop such systems, a framework for virtual preparation and commissioning is presented, with the main goal to offer support for engineers. As traditional virtual commissioning solutions are not intended for preparing highly flexible, collaborative, and dynamic systems, this framework aims to provide some of the groundwork and point to a direction for fast and integrated preparation and virtual commissioning of such systems.Finally, this thesis summarizes some of the investigations made on planning as satisfiability, in order to evaluate how different methods improve planning performance. Throughout the thesis, an industrial material kitting use case exemplifies presented perspectives, lessons learned, and frameworks

A hybrid approach of modular Planning – synchronizing factory and building planning by using component based synthesis

The more and more rising complexity of the industrial environment is triggering companies in a way that is more challenging than ever before. Not only are factory planning projects difficult to handle because of the dynamics and complexity also the necessary planning of the accompanied building gets more and more difficult. To handle this complexity and reduce time and effort for planning as a major factor of success the mainly separately done planning aspects needs to be synchronized. This paper will show an approach of a hybrid factory-building planning method in order to be able to shorten planning time and effort. By using a constraint solving technique the necessary planning tasks are aligned partly automatically and will be processed as a useful planning workflow in form of a gantt diagram for the overall project management

A categorical framework of manufacturing for industry 4.0 and beyond

AbstractWith rapid advancements in industry, technology and applications, many concepts have emerged in manufacturing. It is generally known that the far-sighted term ‘Industry 4.0’ was published to highlight a new industrial revolution. Many manufacturing organizations and companies are researching this topic. However, the achievement criteria of Industry 4.0 are as yet uncertain. In addition, the technology roadmap of accomplishing Industry 4.0 is still not clear in industry nor in academia to date. This paper focuses on the fundamental conception of Industry 4.0 and the state of current manufacturing systems. It also identifies the research gaps between current manufacturing systems and Industry 4.0 requirements. The major contribution is an implementation structure of Industry 4.0, consisting of a multi-layered framework is described, and is shown how it can assist people in understanding and achieving the requirements of Industry 4.0

Digital twin concept applied to simulation and performance reporting for printed circuit board manufacturing

This industrial revolution, also known as Industry 4.0, is now taking place due to technol- ogy requirements. With an ever growing world population, new demands rise, henceforth better, more optimized, more customized, and faster product manufacturing must be achieved. A way to do this is by implementing Smart Manufacturing methods in indus- trial environments, which can be accomplished by using a Digital Twin solution. This dissertation focuses on expanding an already existing Digital Twin, developed by Visteon Corporation, which purpose is to modulate the productive capacity of Visteon’s PCB (Print Circuit Board) production lines. This extension consists of achieving one of the key advantages of using a Digital Twin solution, making predictions regarding a system’s real performance, that in this case, are the production lines. The extension further allows better planning for future changes.A atual revolução industrial, também conhecida como Indústria 4.0, está a ocorrer de- vido a necessidades tecnológicas. Com um aumento constante da população mundial, surgem novas exigências, por isso é necessário alcançar uma melhor, mais otimizada, mais customizada e mais rápida manufatura de produtos. Uma maneira de o fazer é implementando métodos de Smart Manufacturing em ambientes industriais, que pode ser alcançado através de uma solução de Digital Twin. O foco desta dissertação é expandir um Digital Twin já existente, que foi desenvolvido pela Visteon Corporation, cujo objetivo é modular a capacidade produtiva das linhas de produção de PCB (Print Circuit Board) da Visteon. Esta extensão tem como objetivo atingir uma das vantagens mais significativas do uso de uma solução de Digital Twin, fazer previsões da performance real de um sistema, que neste caso, são as linhas de produção. A extensão permite também fazer planeamentos mais rigorosos para o futuro