Enabling Communication Technologies for Automated Unmanned Vehicles in Industry 4.0

Within the context of Industry 4.0, mobile robot systems such as automated guided vehicles (AGVs) and unmanned aerial vehicles (UAVs) are one of the major areas challenging current communication and localization technologies. Due to stringent requirements on latency and reliability, several of the existing solutions are not capable of meeting the performance required by industrial automation applications. Additionally, the disparity in types and applications of unmanned vehicle (UV) calls for more flexible communication technologies in order to address their specific requirements. In this paper, we propose several use cases for UVs within the context of Industry 4.0 and consider their respective requirements. We also identify wireless technologies that support the deployment of UVs as envisioned in Industry 4.0 scenarios.Comment: 7 pages, 1 figure, 1 tabl

Greening Consumer Electronics: Moving Away From Bromine and Chlorine

Presents case studies of seven electronics companies that have engineered environmental solutions that eliminate the use of most brominated and chlorinated chemicals that generate toxic materials. Discusses global standards and regulations

AI and OR in management of operations: history and trends

The last decade has seen a considerable growth in the use of Artificial Intelligence (AI) for operations management with the aim of finding solutions to problems that are increasing in complexity and scale. This paper begins by setting the context for the survey through a historical perspective of OR and AI. An extensive survey of applications of AI techniques for operations management, covering a total of over 1200 papers published from 1995 to 2004 is then presented. The survey utilizes Elsevier's ScienceDirect database as a source. Hence, the survey may not cover all the relevant journals but includes a sufficiently wide range of publications to make it representative of the research in the field. The papers are categorized into four areas of operations management: (a) design, (b) scheduling, (c) process planning and control and (d) quality, maintenance and fault diagnosis. Each of the four areas is categorized in terms of the AI techniques used: genetic algorithms, case-based reasoning, knowledge-based systems, fuzzy logic and hybrid techniques. The trends over the last decade are identified, discussed with respect to expected trends and directions for future work suggested

Power, ERP systems and resistance to management accounting: a case study

This paper reports an intensive longitudinal case study carried out in a Portuguese manufacturing organisation in which attempts to promote change through management accounting were made in recent years. In a first pilot visit to the organisation, two puzzling observations were made. Firstly, and particularly in the manufacturing area of the organisation, management accounting systems introduced in recent years were not being used in everyday interactions and practices. Secondly, a newly introduced ERP system was having no apparent impact on management accounting or on the work of management accountants. We found that these observations were related to issues of power. There were different and conflicting conceptions of which rules should be followed in the manufacturing area, and strategic attempts to enact those conceptions (or to resist alternative ones). This paper draws on the insights of the Circuits of Power (Clegg, 1989a) in order to explain, in theoretically informed manner, the puzzling observations in the case.

Intelligent systems in manufacturing: current developments and future prospects

Global competition and rapidly changing customer requirements are demanding increasing changes in manufacturing environments. Enterprises are required to constantly redesign their products and continuously reconfigure their manufacturing systems. Traditional approaches to manufacturing systems do not fully satisfy this new situation. Many authors have proposed that artificial intelligence will bring the flexibility and efficiency needed by manufacturing systems. This paper is a review of artificial intelligence techniques used in manufacturing systems. The paper first defines the components of a simplified intelligent manufacturing systems (IMS), the different Artificial Intelligence (AI) techniques to be considered and then shows how these AI techniques are used for the components of IMS