Smart Society and Artificial Intelligence: Big Data Scheduling and the Global Standard Method Applied to Smart Maintenance

Abstract The implementation of artificial intelligence (AI) in a smart society, in which the analysis of human habits is mandatory, requires automated data scheduling and analysis using smart applications, a smart infrastructure, smart systems, and a smart network. In this context, which is characterized by a large gap between training and operative processes, a dedicated method is required to manage and extract the massive amount of data and the related information mining. The method presented in this work aims to reduce this gap with near-zero-failure advanced diagnostics (AD) for smart management, which is exploitable in any context of Society 5.0, thus reducing the risk factors at all management levels and ensuring quality and sustainability. We have also developed innovative applications for a human-centered management system to support scheduling in the maintenance of operative processes, for reducing training costs, for improving production yield, and for creating a human–machine cyberspace for smart infrastructure design. The results obtained in 12 international companies demonstrate a possible global standardization of operative processes, leading to the design of a near-zero-failure intelligent system that is able to learn and upgrade itself. Our new method provides guidance for selecting the new generation of intelligent manufacturing and smart systems in order to optimize human–machine interactions, with the related smart maintenance and education

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

Pembangunan Modul Pengajaran Kendiri (MPK) keusahawanan dalam topik isu keusahawanan bagi pelajar diploma di politeknik

Terdapat pelbagai kaedah pembelajaran yang telah diperkenalkan termasuklah kaedah pembelajaran yang menggunakan pendekatan pembelajaran bermodul secara kendiri. Kajian ini adalah bertujuan untuk mengkaji kesesuaian Modul Pengajaran Kendiri Keusahawanan dalam topik Isu Keusahawanan yang telah dihasilkan bagi pelajar yang mengikuti pengajian Diploma di Jabatan Perdagangan Politeknik. Antara aspek yang dikaji ialah untuk menilai sama ada rekabentuk modul yang dihasilkan dapat memenuhi ciri-ciri modul yang baik, MPK yang dihasilkan dapat membantu mencapai objektif pembelajaran, MPK ini bersifat mesra pengguna dan MPK yang dihasilkan membantu pensyarah menyampaikan pengajarannya dengan lebih berkesan. Kajian ini dilakukan ke atas 110 orang pelajar semester en am yang mengikuti pengajian diploma dan 4 orang pensyarah yang mengajar subjek Keusahawanan di Jabatan Perdagangan Politeknik Sultan Salahuddin Abdul Aziz Shah, Selangor. Kaedah analisa data yang digunakan dalam kajian ini ialah skor min dan peratus. Hasil daripada kajian ini menunjukkan bahawa rekabentuk modul yang dihasilkan memenuhi ciri-ciri modul yang baik, MPK ini membantu untuk mencapai objektif pembelajaran, MPK ini bersifat mesra pengguna dan MPK yang dihasilkan dapat membantu pensyarah menyampaikan pengajarannya dengan lebih berkesan. Ini bermakna secara keseluruhannya, hasil kajian menunjukkan bahawa modul yang dihasilkan oleh pengkaji adalah sesuai digunakan oleh pelajar-pelajar semester enam yang mengikuti pengajian diploma di Jabatan Perdagangan peringkat politeknik. Seterusnya, beberapa pandangan telah dikemukakan bagi meningkatkan rnutu dan kualiti MPK yang dihasilkan. Semoga kajian ini dapat memberi manfaat kepada mereka yang terlibat dalam bidang pendidikan

Conclusions and implications of automation in space

Space facilities and programs are reviewed. Space program planning is discussed

A cost-effective intelligent robotic system with dual-arm dexterous coordination and real-time vision

Dexterous coordination of manipulators based on the use of redundant degrees of freedom, multiple sensors, and built-in robot intelligence represents a critical breakthrough in development of advanced manufacturing technology. A cost-effective approach for achieving this new generation of robotics has been made possible by the unprecedented growth of the latest microcomputer and network systems. The resulting flexible automation offers the opportunity to improve the product quality, increase the reliability of the manufacturing process, and augment the production procedures for optimizing the utilization of the robotic system. Moreover, the Advanced Robotic System (ARS) is modular in design and can be upgraded by closely following technological advancements as they occur in various fields. This approach to manufacturing automation enhances the financial justification and ensures the long-term profitability and most efficient implementation of robotic technology. The new system also addresses a broad spectrum of manufacturing demand and has the potential to address both complex jobs as well as highly labor-intensive tasks. The ARS prototype employs the decomposed optimization technique in spatial planning. This technique is implemented to the framework of the sensor-actuator network to establish the general-purpose geometric reasoning system. The development computer system is a multiple microcomputer network system, which provides the architecture for executing the modular network computing algorithms. The knowledge-based approach used in both the robot vision subsystem and the manipulation control subsystems results in the real-time image processing vision-based capability. The vision-based task environment analysis capability and the responsive motion capability are under the command of the local intelligence centers. An array of ultrasonic, proximity, and optoelectronic sensors is used for path planning. The ARS currently has 18 degrees of freedom made up by two articulated arms, one movable robot head, and two charged coupled device (CCD) cameras for producing the stereoscopic views, and articulated cylindrical-type lower body, and an optional mobile base. A functional prototype is demonstrated

Continuous maintenance and the future – Foundations and technological challenges

High value and long life products require continuous maintenance throughout their life cycle to achieve required performance with optimum through-life cost. This paper presents foundations and technologies required to offer the maintenance service. Component and system level degradation science, assessment and modelling along with life cycle ‘big data’ analytics are the two most important knowledge and skill base required for the continuous maintenance. Advanced computing and visualisation technologies will improve efficiency of the maintenance and reduce through-life cost of the product. Future of continuous maintenance within the Industry 4.0 context also identifies the role of IoT, standards and cyber security

Special Session on Industry 4.0

No abstract available

Advancing automation and robotics technology for the Space Station and for the US economy. Volume 1: Executive overview

In response to Public Law 98-371, dated July 18, 1984, the NASA Advanced Technology Advisory Committee has studied automation and robotics for use in the Space Station. The Executive Overview, Volume 1 presents the major findings of the study and recommends to NASA principles for advancing automation and robotics technologies for the benefit of the Space Station and of the U.S. economy in general. As a result of its study, the Advanced Technology Advisory Committee believes that a key element of technology for the Space Station is extensive use of advanced general-purpose automation and robotics. These systems could provide the United States with important new methods of generating and exploiting space knowledge in commercial enterprises and thereby help preserve U.S. leadership in space