Kompetensi pembimbing syarikat bertauliah Sistem Latihan Dual Nasional (SLDN)

Sistem Latihan Dual Nasional (SLDN) merupakan satu sistem latihan dan usahasama antara sektor awam dan sektor swasta dilaksanakan untuk melahirkan tenaga mahir k-worker selari dengan keperluan industri masa kini untuk membangunkan ekonomi negara. Pihak kerajaan dan syarikat swasta menaja pekerja pilihan mereka sebagai pelatih dalam sistem latihan ini bagi mempertingkatkan kebolehan pekerja mereka. Selain itu, pelatih juga terdiri daripada pelajar yang tidak dapat melanjutkan pelajaran ke mana-mana institusi pengajian tinggi awam mahupun swasta. Sistem ini menjalankan pendekatan day release iaitu pelatih menjalani latihan selama empat hari di industri dan satu hari di institusi latihan atau block release iaitu pelatih menjalani latihan kemahiran di industri empat bulan dan satu bulan di institusi latihan mengikut kesesuaian industri tersebut. Kajian berbentuk deskriptif dijalankan untuk melihat melihat tahap kompetensi pembimbing SLDN. Selain itu juga, kajian ini dijalankan bagi melihat perbezaan terhadap tahap pengetahuan, kemahiran dan sikap pembimbing SLDN berdasarkan jantina. Kajian ini juga dibuat bagi menentukan hubungan kompetensi pembimbing berdasarkan pengalaman bekerja. Penyelidikan tinjauan deskriptif ini menggunakan borang soal selidik sebagai instrumen kajian berskala Likert. Seramai 84 orang responden yang terdiri daripada pembimbing syarikat bertauliah SLDN terlibat di dalam kajian ini. Data dianalisis menggunakan SPSS versi 16.0. Hasil analisis mendapati pembimbing mempunyai pengetahuan yang tinggi di samping kemahiran dan sikap. Keputusan inferensi pula menunjukkan tidak terdapat perbezaan antara tahap pengetahuan, kemahiran dan sikap pembimbing berdasarkan jantina manakala analisis korelasi Pearson menunjukkan tidak terdapat hubungan antara kompetensi pembimbing berdasarkan pengalaman bekerja

Quantitative Verification: Formal Guarantees for Timeliness, Reliability and Performance

Computerised systems appear in almost all aspects of our daily lives, often in safety-critical scenarios such as embedded control systems in cars and aircraft or medical devices such as pacemakers and sensors. We are thus increasingly reliant on these systems working correctly, despite often operating in unpredictable or unreliable environments. Designers of such devices need ways to guarantee that they will operate in a reliable and efficient manner. Quantitative verification is a technique for analysing quantitative aspects of a system's design, such as timeliness, reliability or performance. It applies formal methods, based on a rigorous analysis of a mathematical model of the system, to automatically prove certain precisely specified properties, e.g. ``the airbag will always deploy within 20 milliseconds after a crash'' or ``the probability of both sensors failing simultaneously is less than 0.001''. The ability to formally guarantee quantitative properties of this kind is beneficial across a wide range of application domains. For example, in safety-critical systems, it may be essential to establish credible bounds on the probability with which certain failures or combinations of failures can occur. In embedded control systems, it is often important to comply with strict constraints on timing or resources. More generally, being able to derive guarantees on precisely specified levels of performance or efficiency is a valuable tool in the design of, for example, wireless networking protocols, robotic systems or power management algorithms, to name but a few. This report gives a short introduction to quantitative verification, focusing in particular on a widely used technique called model checking, and its generalisation to the analysis of quantitative aspects of a system such as timing, probabilistic behaviour or resource usage. The intended audience is industrial designers and developers of systems such as those highlighted above who could benefit from the application of quantitative verification,but lack expertise in formal verification or modelling

Continuous Improvement Through Knowledge-Guided Analysis in Experience Feedback

Continuous improvement in industrial processes is increasingly a key element of competitiveness for industrial systems. The management of experience feedback in this framework is designed to build, analyze and facilitate the knowledge sharing among problem solving practitioners of an organization in order to improve processes and products achievement. During Problem Solving Processes, the intellectual investment of experts is often considerable and the opportunities for expert knowledge exploitation are numerous: decision making, problem solving under uncertainty, and expert configuration. In this paper, our contribution relates to the structuring of a cognitive experience feedback framework, which allows a flexible exploitation of expert knowledge during Problem Solving Processes and a reuse such collected experience. To that purpose, the proposed approach uses the general principles of root cause analysis for identifying the root causes of problems or events, the conceptual graphs formalism for the semantic conceptualization of the domain vocabulary and the Transferable Belief Model for the fusion of information from different sources. The underlying formal reasoning mechanisms (logic-based semantics) in conceptual graphs enable intelligent information retrieval for the effective exploitation of lessons learned from past projects. An example will illustrate the application of the proposed approach of experience feedback processes formalization in the transport industry sector

Kompetensi pembimbing syarikat bertauliah Sistem Latihan Dual Nasional (SLDN)

Sistem Latihan Dual Nasional (SLDN) merupakan satu sistem latihan dan usahasama antara sektor awam dan sektor swasta dilaksanakan untuk melahirkan tenaga mahir k-worker selari dengan keperluan industri masa kini untuk membangunkan ekonomi negara. Pihak kerajaan dan syarikat swasta menaja pekerja pilihan mereka sebagai pelatih dalam sistem latihan ini bagi mempertingkatkan kebolehan pekerja mereka. Selain itu, pelatih juga terdiri daripada pelajar yang tidak dapat melanjutkan pelajaran ke mana-mana institusi pengajian tinggi awam mahupun swasta. Sistem ini menjalankan pendekatan day release iaitu pelatih menjalani latihan selama empat hari di industri dan satu hari di institusi latihan atau block release iaitu pelatih menjalani latihan kemahiran di industri empat bulan dan satu bulan di institusi latihan mengikut kesesuaian industri tersebut. Kajian berbentuk deskriptif dijalankan untuk melihat melihat tahap kompetensi pembimbing SLDN. Selain itu juga, kajian ini dijalankan bagi melihat perbezaan terhadap tahap pengetahuan, kemahiran dan sikap pembimbing SLDN berdasarkan jantina. Kajian ini juga dibuat bagi menentukan hubungan kompetensi pembimbing berdasarkan pengalaman bekerja. Penyelidikan tinjauan deskriptif ini menggunakan borang soal selidik sebagai instrumen kajian berskala Likert. Seramai 84 orang responden yang terdiri daripada pembimbing syarikat bertauliah SLDN terlibat di dalam kajian ini. Data dianalisis menggunakan SPSS versi 16.0. Hasil analisis mendapati pembimbing mempunyai pengetahuan yang tinggi di samping kemahiran dan sikap. Keputusan inferensi pula menunjukkan tidak terdapat perbezaan antara tahap pengetahuan, kemahiran dan sikap pembimbing berdasarkan jantina manakala analisis korelasi Pearson menunjukkan tidak terdapat hubungan antara kompetensi pembimbing berdasarkan pengalaman bekerja

Deterministic and robust optimisation strategies for metal forming proceesses

Product improvement and cost reduction have always been important goals in the metal forming industry. The rise of\ud Finite Element simulations for metal forming processes has contributed to these goals in a major way. More recently, coupling\ud FEM simulations to mathematical optimisation techniques has shown the potential to make a further contribution to product\ud improvement and cost reduction.\ud Mathematical optimisation consists of the modelling and solving of optimisation problems. Although both the\ud modelling and the solving are essential for successfully optimising metal forming problems, much of the research published until\ud now has focussed on the solving part, i.e. the development of a specific optimisation algorithm and its application to a specific\ud optimisation problem for a specific metal forming process.\ud In this paper, we propose a generally applicable optimisation strategy which makes use of FEM simulations of metal\ud forming processes. It consists of a structured methodology for modelling optimisation problems related to metal forming.\ud Subsequently, screening is applied to reduce the size of the optimisation problem by selecting only the most important design\ud variables. Screening is also utilised to select the best level of discrete variables, which are in such a way removed from the\ud optimisation problem. Finally, the reduced optimisation problem is solved by an efficient optimisation algorithm. The strategy is\ud generally applicable in a sense that it is not constrained to a certain type of metal forming problems, products or processes. Also\ud any FEM code may be included in the strategy.\ud However, the above strategy is deterministic, which implies that the robustness of the optimum solution is not taken\ud into account. Robustness is a major item in the metal forming industry, hence we extended the deterministic optimisation\ud strategy in order to be able to include noise variables (e.g. material variation) during optimisation. This yielded a robust\ud optimisation strategy that enables to optimise to a robust solution of the problem, which contributes significantly to the industrial\ud demand to design robust metal forming processes. Just as the deterministic optimisation strategy, it consists of a modelling,\ud screening and solving stage.\ud The deterministic and robust optimisation strategies are compared to each other by application to an analytical test\ud function. This application emphasises the need to take robustness into account during optimisation, especially in case of\ud constrained optimisation. Finally, both the deterministic and the robust optimisation strategies are demonstrated by application to\ud an industrial hydroforming example

Numerical modeling of the electron beam welding and its experimental validation

Electron Beam Welding (EBW) is a highly efficient and precise welding method increasingly used within the manufacturing chain and of growing importance in different industrial environments such as the aeronautical and aerospace sectors. This is because, compared to other welding processes, EBW induces lower distortions and residual stresses due to the lower and more focused heat input along the welding line. This work describes the formulation adopted for the numerical simulation of the EBW process as well as the experimental work carried out to calibrate and validate it. The numerical simulation of EBW involves the interaction of thermal, mechanical and metallurgical phenomena. For this reason, in this work the numerical framework couples the heat transfer process to the stress analysis to maximize accuracy. An in-house multi-physics FE software is used to deal with the numerical simulation. The definition of an ad hoc moving heat source is proposed to simulate the EB power surface distribution and the corresponding absorption within the work-piece thickness. Both heat conduction and heat radiation models are considered to dissipate the heat through the boundaries of the component. The material behavior is characterized by an apropos thermo-elasto-viscoplastic constitutive model. Titanium-alloy Ti6A14V is the target material of this work. From the experimental side, the EB welding machine, the vacuum chamber characteristics and the corresponding operative setting are detailed. Finally, the available facilities to record the temperature evolution at different thermo-couple locations as well as to measure both distortions and residual stresses are described. Numerical results are compared with the experimental evidence.Peer ReviewedPostprint (author's final draft

Naming the Pain in Requirements Engineering: A Design for a Global Family of Surveys and First Results from Germany

For many years, we have observed industry struggling in defining a high quality requirements engineering (RE) and researchers trying to understand industrial expectations and problems. Although we are investigating the discipline with a plethora of empirical studies, they still do not allow for empirical generalisations. To lay an empirical and externally valid foundation about the state of the practice in RE, we aim at a series of open and reproducible surveys that allow us to steer future research in a problem-driven manner. We designed a globally distributed family of surveys in joint collaborations with different researchers and completed the first run in Germany. The instrument is based on a theory in the form of a set of hypotheses inferred from our experiences and available studies. We test each hypothesis in our theory and identify further candidates to extend the theory by correlation and Grounded Theory analysis. In this article, we report on the design of the family of surveys, its underlying theory, and the full results obtained from Germany with participants from 58 companies. The results reveal, for example, a tendency to improve RE via internally defined qualitative methods rather than relying on normative approaches like CMMI. We also discovered various RE problems that are statistically significant in practice. For instance, we could corroborate communication flaws or moving targets as problems in practice. Our results are not yet fully representative but already give first insights into current practices and problems in RE, and they allow us to draw lessons learnt for future replications. Our results obtained from this first run in Germany make us confident that the survey design and instrument are well-suited to be replicated and, thereby, to create a generalisable empirical basis of RE in practice

SPH method applied to high speed cutting modelling

The purpose of this study is to introduce a new approach of high speed cutting numerical modelling. A Lagrangian smoothed particle hydrodynamics (SPH)- based model is arried out using the Ls-Dyna software. SPH is a meshless method, thus large material distortions that occur in the cutting problem are easily managed and SPH contact control permits a "natural" workpiece/chip separation. The developed approach is compared to machining dedicated code results and experimental data. The SPH cutting model has proved is ability to account for continuous to shear localized chip formation and also correctly estimates the cutting forces, as illustrated in some orthogonal cutting examples. Thus, comparable results to machining dedicated codes are obtained without introducing any adjusting numerical parameters (friction coefficient, fracture control parameter)