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

Permanent-Magnet Synchronous Machine Drives

The permanent-magnet synchronous machine (PMSM) drive is one of best choices for a full range of motion control applications. For example, the PMSM is widely used in robotics, machine tools, actuators, and it is being considered in high-power applications such as industrial drives and vehicular propulsion. It is also used for residential/commercial applications. The PMSM is known for having low torque ripple, superior dynamic performance, high efficiency and high power density. Section 1 deals with the introduction of PMSM and how it is evolved from synchronous motors. Section 2 briefly discusses about the types of PMSM. Section 3 tells about the assumptions in PMSM for modeling of PMSM and it derives the equivalent circuit of PMSM. In Section 4, permanent magnet synchronous motor drive system is briefly discussed with explanation of each blocks in the systems. Section 5 reveals about the control techniques of PMSM like scalar control, vector control and simulation of PMSM driven by field-oriented control using fuzzy logic control with space vector modulation for minimizing torque ripples. PMSM control with and without rotor position sensors along with different control techniques for controlling various parameters of PMSM for different applications is presented in Section 6

Karektor guru pendidikan khas aliran kemahiran berlandaskan nilai retorik dari perspektif pelajar pendidikan khas masalah pendengaran di Malaysia

Latar Belakang: Pendidikan Khas di Malaysia adalah satu usaha yang berterusan untuk melahirkan insan yang berkemahiran, berpandangan jauh, berupaya, beriman, berdikari, mampu merancang dan menguruskan kehidupan harian serta menyedari potensi diri sendiri yang selaras dengan Falsafah Pendidikan Kebangsaan. Aliran pendidikan teknikal dan vokasional juga tidak dikecualikan pelajar yang mempunyai keperluan khas. Oleh itu, guru pendidikan khas aliran kemahiran harus mempunyai karektor yang istimewa untuk mendidik pelajar golongan ini. Namun begitu, masih belum wujudnya satu model standard guru pendidikan khas terutamanya aliran kemahiran. Objektif: Kajian ini dijalankan untuk mengenal pasti tahap penerapan elemen dan dimensi nilai retorik dalam proses pengajaran dan pembelajaran guru aliran kemahiran bagi pelajar pendidikan khas masalah pendengaran. Keputusan: Dapatan kajian ini menunjukkan penerapan elemen nilai retorik ethos dan logos dalam kalangan guru berada pada tahap tinggi, diikuti dengan pathos pada tahap sederhana. Dapatan kajian juga menunjukkan penerapan nilai retorik bagi kebanyakan dimensi pada tahap tinggi, hanya dimensi perasaan dan visualisasi pada tahap sederhana. Kesimpulan: Umumnyaa, guru pendidikan khas aliran kemahiran telah menerapkan nilai retorik pada tahap yang tinggi. Setiap guru digalak untuk menguasai nilai retorik supaya dapat membantu para pelajar menerokai ilmu pengetahuan yang disampaikan oleh mereka dengan berkesan dan seterusnya memberi impak yang positif terhadap pencapaian pelajar

Automatic allocation of safety requirements to components of a software product line

Safety critical systems developed as part of a product line must still comply with safety standards. Standards use the concept of Safety Integrity Levels (SILs) to drive the assignment of system safety requirements to components of a system under design. However, for a Software Product Line (SPL), the safety requirements that need to be allocated to a component may vary in different products. Variation in design can indeed change the possible hazards incurred in each product, their causes, and can alter the safety requirements placed on individual components in different SPL products. Establishing common SILs for components of a large scale SPL by considering all possible usage scenarios, is desirable for economies of scale, but it also poses challenges to the safety engineering process. In this paper, we propose a method for automatic allocation of SILs to components of a product line. The approach is applied to a Hybrid Braking System SPL design

APPLICATION OF ARTIFICIAL NEURAL NETWORKS IN THE CONTEXT OF ACTIVE MAGNETIC BEARING CONTROL SYSTEMS

The article is devoted to the application of neural network methods and genetic algorithms in solving problems of controlling an electric drive of an active magnetic suspension. The method of rolling moment for eliminating an imbalance is considered. The scheme of the neural network controller and the curves of the transients in the open single-mass electromechanical system and in the system c of the neurocontrollers are presented

Optimization techniques for prognostics of on-board electromechanical servomechanisms affected by progressive faults

In relatively recent years, electromechanical actuators (EMAs) have gradually replaced systems based on hydraulic power for flight control applications. EMAs are typically operated by electrical machines that transfer rotational power to the controlled elements (e.g. the aerodynamic control surfaces) by means of gearings and mechanical transmission. Compared to electrohydraulic systems, EMAs offer several advantages, such as reduced weight, simplified maintenance and complete elimination of contaminant, flammable or polluting hydraulic fluids. On-board actuators are often safety critical; then, the practice of monitoring and analyzing the system response through electrical acquisitions, with the aim of estimating fault evolution, has gradually become an essential task of the system engineering. For this purpose, a new discipline, called Prognostics, has been developed in recent years. Its aim is to study methodologies and algorithms capable of identifying such failures and foresee the moment when a particular component loses functionality and is no longer able to meet the desired performance. In this paper, authors introduce the use of optimization techniques in prognostic methods (e.g. model-based parametric estimation algorithms) and propose a new model-based fault detection and identification (FDI) method, based on Genetic Algorithms (GAs) optimization approach, able to perform an early identification of the aforesaid progressive failures, investigating its ability to timely identify symptoms alerting that a component is degrading

A comparative performance analysis based on artificial intelligence techniques applied to three-phase induction motor drives

In this work, we introduced a new robust hybrid control to an induction motor (IM), based on the theory of fuzzy logic and variable structure with sliding-mode control (SMC). As the variations of both control system parameters and operating conditions occur, the conventional control methods may not be satisfied further. Fuzzy tuning schemes are employed to improve control performance and to reduce chattering in the sliding mode. The combination of these two theories has given high performance and fast dynamic response with no overshoot. As it is very robust, it is insensitive to process parameters variation and external disturbances