Kecenderungan kerjaya sebagai usahawan di kalangan pelajar bumiputera di Politeknik Sultan Haji Ahmad Shah, Kuantan, Pahang

Usahawan memainkan peranan penting dalam pembangunan ekonomi sesebuah negara. Walau bagaimanapun, jika dilihat senario sekarang, masih ramai Bumiputera yang kurang berminat untuk menceburi bidang keusahawanan. Justeru itu, kajian ini bertujuan untuk menyelidik tentang tahap kecenderungan keijaya sebagai usahawan di kaiangan pelajar Bumiputera tahun akhir Diploma Akauntansi Politeknik Sultan Haji Ahmad Shah, Kuantan (POLISAS). Secara khususnya, kajian ini akan menyelidik sejauh mana cita-cita pelajar Bumiputera untuk menjadi seorang usahawan dipengaruhi oleh ciri-ciri peribadi pelajar, faktor keluarga, faktor pengajian, pengalaman keija dan faktor persekitaran. Responden kajian terdiri daripada pelajar Bumiputera POLISAS iaitu seramai 51 orang. Data dikumpul menggunakan soal selidik dan dianalisis dengan menggunakan prosedur Ujian T, Crosstabs dan Korelasi Pearson melalui perisian SPSS (Statistical Package For Social Sciences). Dapatan kajian menunjukkan hanya faktor persekitaran (iaitu faktor pihak yang paling mempengaruhi pelajar untuk berniaga) yang dapat menarik minat pelajar untuk melibatkan diri dalam perniagaan. Faktor-faktor lain didapati kurang memberikan sumbangan dalam menarik minat pelajar untuk cenderung kepada bidang keusahawanan. Oleh itu, beberapa cadangan telah dibuat bagi menangani masalah ini agar kaum Bumiputera tidak jauh ketinggalan berbanding kaum lain dan seterusnya memenuhi hasrat kerajaan dalam merealisasikan matlamat Dasar Ekonomi Baru (DEB) yang masih belum dicapai sepenuhnya hingga ke hari ini

Mechatronics in Sustainable Mobility: Two Electric Vehicle Applications

In this paper, we first review the role that mechatronics and advanced control have in modern road vehicles, in particular their present and potential impact on sustainable mobility. We then illustrate this with two research examples. Firstly, we show how electronic science, control system techniques and computing manifest themselves in the design of an advanced battery management algorithm designed to estimate two unmeasurable but vital quantities, State of Charge (SoC) and State of Health (SoH): this allows better utilisation of battery capacity, with scope for advanced prognostics and diagnostics. Secondly, we show how multi-domain modelling integrating mechanical science and electronic science can be used to express component ageing as part of a set of vehicle-level performance objectives and used to explore the trade-offs between conflicting requirements, aiding sensible design choices

Grand Challenges of Traceability: The Next Ten Years

In 2007, the software and systems traceability community met at the first Natural Bridge symposium on the Grand Challenges of Traceability to establish and address research goals for achieving effective, trustworthy, and ubiquitous traceability. Ten years later, in 2017, the community came together to evaluate a decade of progress towards achieving these goals. These proceedings document some of that progress. They include a series of short position papers, representing current work in the community organized across four process axes of traceability practice. The sessions covered topics from Trace Strategizing, Trace Link Creation and Evolution, Trace Link Usage, real-world applications of Traceability, and Traceability Datasets and benchmarks. Two breakout groups focused on the importance of creating and sharing traceability datasets within the research community, and discussed challenges related to the adoption of tracing techniques in industrial practice. Members of the research community are engaged in many active, ongoing, and impactful research projects. Our hope is that ten years from now we will be able to look back at a productive decade of research and claim that we have achieved the overarching Grand Challenge of Traceability, which seeks for traceability to be always present, built into the engineering process, and for it to have "effectively disappeared without a trace". We hope that others will see the potential that traceability has for empowering software and systems engineers to develop higher-quality products at increasing levels of complexity and scale, and that they will join the active community of Software and Systems traceability researchers as we move forward into the next decade of research

Grand Challenges of Traceability: The Next Ten Years

In 2007, the software and systems traceability community met at the first Natural Bridge symposium on the Grand Challenges of Traceability to establish and address research goals for achieving effective, trustworthy, and ubiquitous traceability. Ten years later, in 2017, the community came together to evaluate a decade of progress towards achieving these goals. These proceedings document some of that progress. They include a series of short position papers, representing current work in the community organized across four process axes of traceability practice. The sessions covered topics from Trace Strategizing, Trace Link Creation and Evolution, Trace Link Usage, real-world applications of Traceability, and Traceability Datasets and benchmarks. Two breakout groups focused on the importance of creating and sharing traceability datasets within the research community, and discussed challenges related to the adoption of tracing techniques in industrial practice. Members of the research community are engaged in many active, ongoing, and impactful research projects. Our hope is that ten years from now we will be able to look back at a productive decade of research and claim that we have achieved the overarching Grand Challenge of Traceability, which seeks for traceability to be always present, built into the engineering process, and for it to have "effectively disappeared without a trace". We hope that others will see the potential that traceability has for empowering software and systems engineers to develop higher-quality products at increasing levels of complexity and scale, and that they will join the active community of Software and Systems traceability researchers as we move forward into the next decade of research

Negotiating disciplinary boundaries in engineering problem-solving practice

Includes bibliographical referencesThe impetus for this research is the well-documented current inability of Higher Education to facilitate the level of problem solving required in 21st century engineering practice. The research contends that there is insufficient understanding of the nature of and relationship between the significantly different forms of disciplinary knowledge underpinning engineering practice. Situated in the Sociology of Education, and drawing on the social realist concepts of knowledge structures (Bernstein, 2000) and epistemic relations (Maton, 2014), the research maps the topology of engineering problem-solving practice in order to illuminate how novice problem solvers engage in epistemic code shifting in different industrial contexts. The aim in mapping problem-solving practices from an epistemological perspective is to make an empirical contribution to rethinking the theory/practice relationship in multidisciplinary engineering curricula and pedagogy, particularly at the level of technician. A novel and pragmatic problem-solving model - integrated from a range of disciplines - forms the organising framework for a methodologically pluralist case-study approach. The research design draws on a metaphor from the empirical site (modular automation systems) and sees the analysis of twelve matched cases in three categories. Case-study data consist of questionnaire texts, re-enactment interviews, expert verification interviews, and industry literature. The problem-solving model components (problem solver, problem environment, problem structure and problem-solving process) were analysed using, primarily, the Legitimation Code Theory concept of epistemic relations. This is a Cartesian plane-based instrument describing the nature of and relations between a phenomenon (what) and ways of approaching the phenomenon (how). Data analyses are presented as graphical relational maps of different practitioner knowledge practices in different contexts across three problem solving stages: approach, analysis and synthesis. Key findings demonstrate a symbiotic, structuring relationship between the 'what' and the 'how' of the problem in relation to the problem-solving components. Successful problem solving relies on the recognition of these relationships and the realisation of appropriate practice code conventions, as held to be legitimate both epistemologically and contextually. Successful practitioners engage in explicit code-shifting, generally drawing on a priori physics and mathematics-based knowledge, while acquiring a posteriori context-specific logic-based knowledge. High-achieving practitioners across these disciplinary domains demonstrate iterative code-shifting practices and discursive sensitivity. Recommendations for engineering education include the valuing of disciplinary differences and the acknowledgement of contextual complexity. It is suggested that the nature of engineering mathematics as currently taught and the role of mathematical thinking in enabling successful engineering problem-solving practice be investigated

Conceptual Key Competency Model for Smart Factories in Production Processes

AbstractBackground and Purpose: The aim of the study is to develop a conceptual key competency model for smart factories in production processes, focused on the automotive industry, as innovation and continuous development in this industry are at the forefront and represent the key to its long-term success.Methodology: For the purpose of the research, we used a semi-structured interview as a method of data collection. Participants were segmented into three homogeneous groups, which are industry experts, university professors and secondary education teachers, and government experts. In order to analyse the qualitative data, we used the method of content analysis.Results: Based on the analysis of the data collected by structured interviews, we identified the key competencies that workers in smart factories in the automotive industry will need. The key competencies are technical skills, ICT skills, innovation and creativity, openness to learning, ability to accept and adapt to change, and various soft skills.Conclusion: Our research provides insights for managers working in organisations that are transformed by Industry 4.0. For instance, human resource managers can use our results to study what competencies potential candidates need to perform well on the job, particularly in regards to planning future job profiles in regards related to production processes. Moreover, they can design competency models in a way that is coherent with the trends of Industry 4.0. Educational policy makers should design curricula that develop mentioned competencies. In the future, the results presented here can be compared and contrasted with findings obtained by applying other empirical methods

Integrated platform for real-time control and production and productivity monitoring and analysis

In this paper is proposed the IndustSystems, which is an integrated platform that aims at controlling and monitoring of production and evaluation of productivity in real time, via web access, using hybrid and scheduling algorithms that allow management and optimized use of production resources and perfect synchronization of production flows.This work was supported by FCT “Fundação para a Ciência e a Tecnologia” under the program: PEst20152020.info:eu-repo/semantics/publishedVersio

Industrial, Collaborative and Mobile Robotics in Latin America: Review of Mechatronic Technologies for Advanced Automation

Mechatronics and Robotics (MaR) have recently gained importance in product development and manufacturing settings and applications. Therefore, the Center for Space Emerging Technologies (C-SET) has managed an international multi-disciplinary study to present, historically, the first Latin American general review of industrial, collaborative, and mobile robotics, with the support of North American and European researchers and institutions. The methodology is developed by considering literature extracted from Scopus, Web of Science, and Aerospace Research Central and adding reports written by companies and government organizations. This describes the state-of-the-art of MaR until the year 2023 in the 3 Sub-Regions: North America, Central America, and South America, having achieved important results related to the academy, industry, government, and entrepreneurship; thus, the statistics shown in this manuscript are unique. Also, this article explores the potential for further work and advantages described by robotic companies such as ABB, KUKA, and Mecademic and the use of the Robot Operating System (ROS) in order to promote research, development, and innovation. In addition, the integration with industry 4.0 and digital manufacturing, architecture and construction, aerospace, smart agriculture, artificial intelligence, and computational social science (human-robot interaction) is analyzed to show the promising features of these growing tech areas, considering the improvements to increase production, manufacturing, and education in the Region. Finally, regarding the information presented, Latin America is considered an important location for investments to increase production and product development, taking into account the further proposal for the creation of the LATAM Consortium for Advanced Robotics and Mechatronics, which could support and work on roboethics and education/R+D+I law and regulations in the Region. Doi: 10.28991/ESJ-2023-07-04-025 Full Text: PD

Decomposition of automotive manufacturing machines through a mechanism taxonomy within a product lifecycle management framework

The automotive sector as with other manufacturing industries is under continual pressure from the consumer to deliver greater levels of product customisation at a higher quality and at reduced costs. Maintaining market position is therefore increasingly determined by a company's ability to innovate design changes quickly and produce greater numbers of product variants on leaner production lines with shorter times to market. In response manufacturers are attempting to accommodate product customisation and change through the use of reconfigurable production machines. Besides the need for flexibility, production facilities represent a significant investment for automotive manufacturers which is increasingly critical to commercial success; consequently the need to reduce costs through the reuse of assembly and manufacturing hardware on new product programs is becoming crucial. The aim of this research is to enable production machines to be more easily and cost effectively built and subsequently reconfigurable through the adoption of a component-based approach to their implementation utilising virtual manufacturing tools such as Product Lifecycle Management (PLM). It is suggested that through the decomposition of manufacturing machines into standardised mechanisms and their associated data structures a revised business model can be defined. The mechanisms are classified and deployed as part of a consistent integrated data structure that encompasses product, process and plant information. An objective is to properly integrate manufacturing data with more established Product Data Management (PDM) processes. The main areas of research reported in this article are, (1) development of a method for identifying and mapping data producers, consumers and flow, (2) development of standardised data structures for the management of manufacturing data within a PLM tool, (3) development of a taxonomy for the decomposition of manufacturing and assembly lines into a library of standard physical, logical and structural mechanisms and their associated interfaces. An automotive OEM case study is presented to illustrate the classification and management of production mechanisms focusing on an engine assembly line