Identifying smart design attributes for Industry 4.0 customization using a clustering Genetic Algorithm

Industry 4.0 aims at achieving mass customization at a mass production cost. A key component to realizing this is accurate prediction of customer needs and wants, which is however a challenging issue due to the lack of smart analytics tools. This paper investigates this issue in depth and then develops a predictive analytic framework for integrating cloud computing, big data analysis, business informatics, communication technologies, and digital industrial production systems. Computational intelligence in the form of a cluster k-means approach is used to manage relevant big data for feeding potential customer needs and wants to smart designs for targeted productivity and customized mass production. The identification of patterns from big data is achieved with cluster k-means and with the selection of optimal attributes using genetic algorithms. A car customization case study shows how it may be applied and where to assign new clusters with growing knowledge of customer needs and wants. This approach offer a number of features suitable to smart design in realizing Industry 4.0

An Inquiry into the Status and Nature of University-Industry Research Collaborations in Japan and Korea

University-industry collaboration (UIC) has become an increasingly frequent innovation strategy, especially in the Western hemisphere. But we know much less about such research collaborations in East Asia. This study explores and contrasts the current nature and status of UICs in Japan and Korea focusing on factors that facilitate the development and management of such research linkages. The findings indicate that UICs are path dependent, i.e. firms benefit from their experience with previous projects when collaborating with universities. At the same time, cultural factors appear to result in significant differences in the organization of UICs in Japan and Korea.University-industry collaboration, R&D collaboration, International comparison, Japan, Korea

Multi Agent Systems in Logistics: A Literature and State-of-the-art Review

Based on a literature survey, we aim to answer our main question: “How should we plan and execute logistics in supply chains that aim to meet today’s requirements, and how can we support such planning and execution using IT?†Today’s requirements in supply chains include inter-organizational collaboration and more responsive and tailored supply to meet specific demand. Enterprise systems fall short in meeting these requirements The focus of planning and execution systems should move towards an inter-enterprise and event-driven mode. Inter-organizational systems may support planning going from supporting information exchange and henceforth enable synchronized planning within the organizations towards the capability to do network planning based on available information throughout the network. We provide a framework for planning systems, constituting a rich landscape of possible configurations, where the centralized and fully decentralized approaches are two extremes. We define and discuss agent based systems and in particular multi agent systems (MAS). We emphasize the issue of the role of MAS coordination architectures, and then explain that transportation is, next to production, an important domain in which MAS can and actually are applied. However, implementation is not widespread and some implementation issues are explored. In this manner, we conclude that planning problems in transportation have characteristics that comply with the specific capabilities of agent systems. In particular, these systems are capable to deal with inter-organizational and event-driven planning settings, hence meeting today’s requirements in supply chain planning and execution.supply chain;MAS;multi agent systems

Internet of robotic things : converging sensing/actuating, hypoconnectivity, artificial intelligence and IoT Platforms

The Internet of Things (IoT) concept is evolving rapidly and influencing newdevelopments in various application domains, such as the Internet of MobileThings (IoMT), Autonomous Internet of Things (A-IoT), Autonomous Systemof Things (ASoT), Internet of Autonomous Things (IoAT), Internetof Things Clouds (IoT-C) and the Internet of Robotic Things (IoRT) etc.that are progressing/advancing by using IoT technology. The IoT influencerepresents new development and deployment challenges in different areassuch as seamless platform integration, context based cognitive network integration,new mobile sensor/actuator network paradigms, things identification(addressing, naming in IoT) and dynamic things discoverability and manyothers. The IoRT represents new convergence challenges and their need to be addressed, in one side the programmability and the communication ofmultiple heterogeneous mobile/autonomous/robotic things for cooperating,their coordination, configuration, exchange of information, security, safetyand protection. Developments in IoT heterogeneous parallel processing/communication and dynamic systems based on parallelism and concurrencyrequire new ideas for integrating the intelligent “devices”, collaborativerobots (COBOTS), into IoT applications. Dynamic maintainability, selfhealing,self-repair of resources, changing resource state, (re-) configurationand context based IoT systems for service implementation and integrationwith IoT network service composition are of paramount importance whennew “cognitive devices” are becoming active participants in IoT applications.This chapter aims to be an overview of the IoRT concept, technologies,architectures and applications and to provide a comprehensive coverage offuture challenges, developments and applications

DRIVER Technology Watch Report

This report is part of the Discovery Workpackage (WP4) and is the third report out of four deliverables. The objective of this report is to give an overview of the latest technical developments in the world of digital repositories, digital libraries and beyond, in order to serve as theoretical and practical input for the technical DRIVER developments, especially those focused on enhanced publications. This report consists of two main parts, one part focuses on interoperability standards for enhanced publications, the other part consists of three subchapters, which give a landscape picture of current and surfacing technologies and communities crucial to DRIVER. These three subchapters contain the GRID, CRIS and LTP communities and technologies. Every chapter contains a theoretical explanation, followed by case studies and the outcomes and opportunities for DRIVER in this field

Facilitating Distinctive and Meaningful Change Within U.S. Law Schools (Part 2): Pursuing Successful Plan Implementation Through Better Resource Management

In Part 1 of this series, one of the current authors used institutional theory, behavioral economics, and psychology to explain why U.S. law schools have had difficulty evolving faster and better. The author then used institutional entrepreneurship to propose a seven-step, faculty-led, operational change process designed to overcome institutional isomorphism and to enable each law school to formulate a distinctive, meaningful, strategic plan. In Part 2, the current article addresses the typical implementation challenges to be expected within the context of existing law school governance. The article begins by discussing the Resource Based View of the firm and the role of resource management in achieving competitive advantages. These considerations lay the foundation for the critical role of faculty engagement and law school leadership in successful strategic plan implementation. Next, within this context, the article discusses four questions whose answers may foreshadow implementation problems. Lastly, the article discusses the results of several Monte Carlo Simulations. The simulations provide insight into the likely performance problems caused by faculty misaligned with, or disengaged from, their law school’s strategic goals. The results suggest that even minimal faculty misalignment can have a significant deleterious effect on the ability of a given law school to achieve any distinctive position. All told, the article concludes that U.S. law schools can successfully implement distinctive and meaningful strategic plans within existing shared governance structures. However, success will be difficult to achieve. It requires the full engagement and leadership by both the faculty and the Dean, sustained operational support for strategic change, and the active management of law school resources

Managing Intellectual Property to Foster Agricultural Development

Over the past decades, consideration of IPRs has become increasingly important in many areas of agricultural development, including foreign direct investment, technology transfer, trade, investment in innovation, access to genetic resources, and the protection of traditional knowledge. The widening role of IPRs in governing the ownership of—and access to—innovation, information, and knowledge makes them particularly critical in ensuring that developing countries benefit from the introduction of new technologies that could radically alter the welfare of the poor. Failing to improve IPR policies and practices to support the needs of developing countries will eliminate significant development opportunities. The discussion in this note moves away from policy prescriptions to focus on investments to improve how IPRs are used in practice in agricultural development. These investments must be seen as complementary to other investments in agricultural development. IPRs are woven into the context of innovation and R&D. They can enable entrepreneurship and allow the leveraging of private resources for resolving the problems of poverty. Conversely, IPRs issues can delay important scientific advancements, deter investment in products for the poor, and impose crippling transaction costs on organizations if the wrong tools are used or tools are badly applied. The central benefit of pursuing the investments outlined in this note is to build into the system a more robust capacity for strategic and flexible use of IPRs tailored to development goals

Construction of PAI Learning Model Based on Knowledge Society at UIN Satu Tulungagung and IAIN Kediri, Indonesia

This article aims to explore the construction of knowledge society-based PAI learning models in Islamic Religious Colleges (PTKI). This article was compiled based on qualitative research with a case study type. The locus of this research is UIN SATU Tulungagung and IAIN Kediri. Data collection methods used by researchers are interviews, observation, and documentation. The data analysis technique in this study is descriptive-analysis and content analysis. The flow used in interpreting this research is a qualitative data analysis technique with an interactive model proposed by Miles-Huberman, including the stages of data collection, reduction, data display, and conclusion drawing. This article concludes that the competence of lecturers in the use of IT and the various competencies of students are still the biggest obstacles faced by UIN SATU Tulungagung and IAIN Kediri in implementing knowledge society-based PAI learning. In addition, the academic culture on both campuses has not run optimally. The two campuses have the same construction of the knowledge society-based Islamic education learning model, especially in terms of enforcing academic freedom in the lecture process, routinely discussing Islamic religious education lecturers to equalize perceptions in providing inclusive PAI material within the moderation frame, and optimizing the use of IT for Islamic Islamic education lectures. What makes the difference is that UIN SATU Tulungagung implements knowledge society-based PAI learning by applying a collaborative learning model to the lecture process. Meanwhile, IAIN Kediri focuses on implementing the cooperative learning model to optimize PAI learning in the classroom

Management of Cluster Policies: Case Studies of Japanese, German, and French Bio-clusters

This paper provides a detailed comparison of the following five cases of Japanese and European clusters in biotechnology: (1) Kobe Biomedical Innovation Cluster (KBIC) in Kobe (Japan), (2) Fuji Pharma Valley Cluster in Shizuoka Prefecture (Japan), (3) BioM Biotech Cluster in Munich (Germany), (4) BioRegion Rhine-Neckar in Heidelberg (Germany), and (5) Alsace BioValley Cluster in Strasbourg (France). We pay special attention to the cluster policy and its management by each region's core cluster management organization. Information on the focal clusters and the management of cluster policies has been obtained through interviews with the cluster directors and core staff in 2010 and 2011. We find several similarities and differences among the five cases of Japanese and European clusters. We also discuss how the management of cluster policies by the core management organizations may be related with the performance of regional clusters.management, cluster policy, regional cluster, R&D, biotechnology, international comparison