Saeed Abdolshah

Barriers to the successful implementation of TQM in Iranian manufacturing organisations

TQM is a set of management practices throughout the organisation, geared to ensure the organisation consistently meets or exceeds customer requirements. This research tries to investigate the most important barriers to successful TQM implementation in Iranian manufacturing organisations. The authors have studied samples of manufacturing organisations, comprising those that have invested on TQM after the end of March 2009 and were located in Iran. This descriptive and cross-sectional research is carried out via two questionnaires – general questionnaire for success of TQM principles and specific questionnaire for barriers to successful TQM implementation. The statistical population of this research consists of all managers of manufacturing organisations who implemented TQM in their organisations. Results showed that the main root causes of unsuccessful implementation of TQM were the lack of management commitment, resource problem and failure to use the right framework for TQM. In addition, there is a significant coincidence between the results of two questionnaires. Finally, regarding the findings of this research, we offer a relation between TQM principles and barriers to successful TQM implementation. Therefore, in order to reduce the barriers to successful TQM implementation, some suggestions were proposed.

First Experimental Testing of a Dynamic Minimum Tension Control (DMTC) for Cable Driven Parallel Robots

Cable tension distribution is an important issue in parallel cable-driven robots to obtain high efficiency and accuracy of motion. In this paper, a novel approach is introduced to optimize cable tension distribution of cable-driven parallel robots, which consists in modifying the minimum tension of the cables according to the dynamics of the system. This method has been compared to the traditional, fixed-minimum tension approach on a 2-cable, 1 DOF test bed with different settings of the controller. First experimental results showed that Dynamic Minimum Tension Control (DMTC) can be better than traditional approaches in terms of accuracy and energy consumption.

Analysis of upper extremity motion during trip-induced falls

Forward fall is one of the most common causes of upper extremity fractures. Significant factors influencing impact force and injuries were widely studied; however, it is necessary to investigate the natural reactions of humans during a forward fall to obtain a realistic evaluation of injuries. The purpose of this study was to analyze the natural motion of the upper extremity during an induced trip. We carried out a tripping experiment using an obstacle colliding with one leg; while recovery step was prevented to produce a forward fall. Results showed that the elbow extension had a slight ascending trend during the forward fall and elbow angle at the moment of hand-ground contact was appropriate to reduce the peak force. Landing on the obstacle-side hand was more likely due to body rotation towards the obstacle-side. To prevent injuries, subjects were connected to a safety harness not to strike the ground with high impact velocity. Thus, the fall motion was simulated using a 12 DOF model to obtain a realistic evaluation of the impact velocity and the related impact force caused by the forward fall was estimated using a sagittal 3-segment model. Results of this study can be useful in human-robot collaboration, where a collision between human and robot may cause a forward fall.

Performance evaluation of a new design of cable-suspended camera system

Adaptive cable-driven parallel robots can adjust the position of one or more pulley blocks to optimize performance within a given workspace. Because of their augmented kinematic redundancy, adaptive systems have several advantages over their traditional counterparts featuring the same numbers of cables. In this paper, we explore the application of adaptive cable-driven robots to cable-suspended camera systems. Performance of the traditional and of the adaptive designs are analyzed, using dexterity and stiffness as performance metrics. Results show superior performance of the adaptive design compared to the traditional system. An illustrative design problem for adaptive cable-suspended camera systems is also presented and solved.

Developing a computer vision method based on AHP and feature ranking for ores type detection

Graphical abstractDisplay Omitted HighlightsUnique way in combination of neural networks with the analytic hierarchy process.Utilizing the experts point of view for improving and weighting the features.Using creative and new extracted features in minerals images.Unique way of time and space complexity optimization by ranking the features.Acquiring performance and accuracy higher than the related papers in this scope. Detection of size, shape and color of minerals are important for obtaining information about minerals. The output of mines is ores which vary in colors and shapes. The multiplicity of ores, large scale features and the importance of speeding up the mineral type detection process for intelligent systems, leads us to rely more on experts advice and rank the selected available features for type detection, according to their importance. In this paper, to separate different ores and gangue minerals, image processing and computer vision techniques with combination of multi criteria decision making (MCDM) approach are applied. Our method proposes a novel way which combines the image processing techniques and artificial neural networks, with analytic hierarchy process (AHP) approaches to detect different types of ores. By help of experts in feature ranking, the image processing techniques proved to be more effective and prompt. The final results show that the proposed method is more successful in type detection of minerals than the other image processing techniques for ores type detection. Our method is also applicable for real-time systems to estimate minerals at on-line ore sorting and classification stages.