Product lifecycle management with knowledge management as a strategic approach for innovative enterprise environment

Process planning knowledge (PPK) is one of the most important knowledge in production manufacturing enterprise. This paper analyzes the PPK and the concept of process planning information model (PPIM) implemented in production enterprise. In second part of the paper, there is done the basic information about PLM concept as a business strategy for product development where are included PPK and PPIM approaches, strategy which offer possibilities for innovation. Product Lifecycle Management (PLM) is the process of managing the whole life cycle of a product starting from generating an idea, concept description, business analyzes, product design, solution architecture and technical implementation, to the successful entrance to the market, service, maintenance and innovative product improvement

Towards the integration of enterprise software: The business manufacturing intelligence

Nowadays, the Information Communication Technology has pervaded literally the companies. In the company circulates an huge amount of information but too much information doesn’t provide any added value. The overload of information exceeds individual processing capacity and slowdowns decision making operations. We must transform the enormous quantity of information in useful knowledge taking in consideration that information becomes obsolete quickly in condition of dynamic market. Companies process this information by specific software for managing, efficiently and effectively, the business processes. In this paper we analyse the myriad of acronyms of software that is used in enterprises with the changes that occurred over the time, from production to decision making until to convergence in an intelligent modular enterprise software, that we named Business Manufacturing Intelligence (BMI), that will manage and support the enterprise in the futurebusiness manufacturing intelligence, enterprise resource planning; business intelligence; management software; automation software; decision making software

Study on interoperation and its' implementation of MES to support virtual factory

© 2020 Published under licence by IOP Publishing Ltd. The data interoperation between VF (virtual factory) platform and MES (Manufacturing Execution System) plays an important role in intelligent factory construction. The study focuses on the integration strategy between the VF and the MES by incorporating VF manufacturing assets in two ways, i.e., vertical integration (used for production line performance evaluation) and the horizontal integration (cloud manufacturing based on manufacturing assets services discovery and their composition). The VF platform which integrates the manufacturing assets in two manners is designed as the bottom layer in the entire integration framework. It has been applied to build a four tiers integration model in an intelligent production system construction of a domestic ship manufacturer and verified its feasibility and availability

Learning from the lifecycle:The capabilities and limitations of current product lifecycle practice and systems

Design teams within the High Value Low Volume (HVLV) industry are facing ever-increasing challenges in developing new products. This has been largely due to the paradigm shift towards Product Service Systems, the growing importance of demonstrating Corporate Social Responsibility and stricter environmental legislation. With the variant nature of the design process within the HVLV industry and the longevity of the product life-cycles, it is recognised that learning from previous products is essential for new product innovation and development. The ability to do this depends upon the company’s product lifecycle practice and systems, and its inherent capability/limitations. To explore these issues, this paper maps typical data and information flow and the Information Systems involved, onto a generalised product lifecycle for HVLV. The map is generated from an extensive literature review and is used to critically appraise and reflect upon current product data lifecycle practice. In particular, its capability to provide design teams in the HVLV industries with sufficient data and information throughout the lifecycle phases of existing products to inform variant product design is considered

Learning from the lifecycle: The current capabilities and limitations of product lifecycle practice and systems

Design teams within the High Value Low Volume (HVLV) industry are facing ever-increasing challenges in developing new products. This has been largely due to the paradigm shift towards Product Service Systems, the growing importance of demonstrating Corporate Social Responsibility and stricter environmental legislation. With the variant nature of the design process within the HVLV industry and the longevity of the product life-cycles, it is recognised that learning from previous products is essential for new product innovation and development. The ability to do this depends upon the company’s product lifecycle practice and systems, and its inherent capability/limitations. To explore these issues, this paper maps typical data and information flow and the Information Systems involved, onto a generalised product lifecycle for HVLV. The map is generated from an extensive literature review and is used to critically appraise and reflect upon current product data lifecycle practice. In particular, its capability to provide design teams in the HVLV industries with sufficient data and information throughout the lifecycle phases of existing products to inform variant product design is considered

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

Mining Event Logs to Support Workflow Resource Allocation

Workflow technology is widely used to facilitate the business process in enterprise information systems (EIS), and it has the potential to reduce design time, enhance product quality and decrease product cost. However, significant limitations still exist: as an important task in the context of workflow, many present resource allocation operations are still performed manually, which are time-consuming. This paper presents a data mining approach to address the resource allocation problem (RAP) and improve the productivity of workflow resource management. Specifically, an Apriori-like algorithm is used to find the frequent patterns from the event log, and association rules are generated according to predefined resource allocation constraints. Subsequently, a correlation measure named lift is utilized to annotate the negatively correlated resource allocation rules for resource reservation. Finally, the rules are ranked using the confidence measures as resource allocation rules. Comparative experiments are performed using C4.5, SVM, ID3, Na\"ive Bayes and the presented approach, and the results show that the presented approach is effective in both accuracy and candidate resource recommendations.Comment: T. Liu et al., Mining event logs to support workflow resource allocation, Knowl. Based Syst. (2012), http://dx.doi.org/ 10.1016/j.knosys.2012.05.01

Web-based strategies in the manufacturing industry

The explosive growth of Internet-based architectures is allowing an efficient access to information resources over geographically dispersed areas. This fact is exerting a major influence on current manufacturing practices. Business activities involving customers, partners, employees and suppliers are being rapidly and efficiently integrated through networked information management environments. Therefore, efforts are required to take advantage of distributed infrastructures that can satisfy information integration and collaborative work strategies in corporate environments. In this research, Internet-based distributed solutions focused on the manufacturing industry are proposed. Three different systems have been developed for the tooling sector, specifically for the company Seco Tools UK Ltd (industrial collaborator). They are summarised as follows. SELTOOL is a Web-based open tool selection system involving the analysis of technical criteria to establish appropriate selection of inserts, toolholders and cutting data for turning, threading and grooving operations. It has been oriented to world-wide Seco customers. SELTOOL provides an interactive and crossed-way of searching for tooling parameters, rather than conventional representation schemes provided by catalogues. Mechanisms were developed to filter, convert and migrate data from different formats to the database (SQL-based) used by SELTOOL.TTS (Tool Trials System) is a Web-based system developed by the author and two other researchers to support Seco sales engineers and technical staff, who would perform tooling trials in geographically dispersed machining centres and benefit from sharing data and results generated by these tests. Through TTS tooling engineers (authorised users) can submit and retrieve highly specific technical tooling data for both milling and turning operations. Moreover, it is possible for tooling engineers to avoid the execution of new tool trials knowing the results of trials carried out in physically distant places, when another engineer had previously executed these trials. The system incorporates encrypted security features suitable for restricted use on the World Wide Web. An urgent need exists for tools to make sense of raw data, extracting useful knowledge from increasingly large collections of data now being constructed and made available from networked information environments. This explosive growth in the availability of information is overwhelming the capabilities of traditional information management systems, to provide efficient ways of detecting anomalies and significant patterns in large sets of data. Inexorably, the tooling industry is generating valuable experimental data. It is a potential and unexplored sector regarding the application of knowledge capturing systems. Hence, to address this issue, a knowledge discovery system called DISKOVER was developed. DISKOVER is an integrated Java-application consisting of five data mining modules, able to be operated through the Internet. Kluster and Q-Fast are two of these modules, entirely developed by the author. Fuzzy-K has been developed by the author in collaboration with another research student in the group at Durham. The final two modules (R-Set and MQG) have been developed by another member of the Durham group. To develop Kluster, a complete clustering methodology was proposed. Kluster is a clustering application able to combine the analysis of quantitative as well as categorical data (conceptual clustering) to establish data classification processes. This module incorporates two original contributions. Specifically, consistent indicators to measure the quality of the final classification and application of optimisation methods to the final groups obtained. Kluster provides the possibility, to users, of introducing case-studies to generate cutting parameters for particular Input requirements. Fuzzy-K is an application having the advantages of hierarchical clustering, while applying fuzzy membership functions to support the generation of similarity measures. The implementation of fuzzy membership functions helped to optimise the grouping of categorical data containing missing or imprecise values. As the tooling database is accessed through the Internet, which is a relatively slow access platform, it was decided to rely on faster Information retrieval mechanisms. Q-fast is an SQL-based exploratory data analysis (EDA) application, Implemented for this purpose

Taxonomy and uncertainties of cloud manufacturing

The manufacturing industry is currently undergoing rapid changes because of the rapid growth of advanced technologies in information systems and networks, which allow for collaboration around the world. This combination of the latest information technologies and advanced manufacturing networks has led to the growth of a new manufacturing model known as cloud manufacturing. Because cloud manufacturing is considered an emerging research area, there are significant gaps in the literature regarding the concept of cloud manufacturing, its implementation, and in particular the uncertainties coming with this new technology. This research aims to explain the concept of cloud manufacturing, its capabilities and potential. This work also introduces cloud manufacturing taxonomy, and investigates uncertainties that come with employing cloud manufacturing. Finally, proposals for future research in the context of cloud manufacturing are presented to address opportunities in cloud manufacturing

Integration of decision support systems to improve decision support performance

Decision support system (DSS) is a well-established research and development area. Traditional isolated, stand-alone DSS has been recently facing new challenges. In order to improve the performance of DSS to meet the challenges, research has been actively carried out to develop integrated decision support systems (IDSS). This paper reviews the current research efforts with regard to the development of IDSS. The focus of the paper is on the integration aspect for IDSS through multiple perspectives, and the technologies that support this integration. More than 100 papers and software systems are discussed. Current research efforts and the development status of IDSS are explained, compared and classified. In addition, future trends and challenges in integration are outlined. The paper concludes that by addressing integration, better support will be provided to decision makers, with the expectation of both better decisions and improved decision making processes