Applied Mechanics and Materials Vols. 789-790

Abstract: An assembly system consists of work stations where specific tasks are carried in such a way that last station gives the complete product. An assembly line balancing Problem (ALBP) involves optimally assigning tasks among workstations with respect to some performance objective. ALBP problems are of NP hard nature and in literature; many efforts are there to solve the problem efficiently through heuristics. This paper proposes a heuristic algorithm for solving type 2 ALBP for single objective optimization. The proposed algorithm assigns tasks to a fixed no of stations with objective of minimizing cycle time. In literature, type 2 ALBP is mostly solved through Type 1 problem. However, this paper proposes a direct approach to Type 2 ALBP. The effectiveness is tested through application on Gunther problem of 35 tasks with forty five precedence constraints. The task assignment for six stations is computed and it shows competitive performance. The number of fixed stations is varied and corresponding cycle times are computed. The algorithm is also tested on a real industrial problem of 24 tasks. The experimental testing indicates tendency of the proposed algorithm to give effective optimal results.

Abstract: Systematic achievement of high productivity lapping entails conceiving of a robust working system, insensitive to the action of disturbing factors. The experiments described in this paper were aimed at configuring such a robust machining system in view of maximising productivity. The main purpose of the experiments was to identify an optimum combination of the values of the input quantities of the machining system, such as to achieve its robustness, that is rendering it insensitive to the action of noise factors.

Abstract: Recent literature shows that most safety-related standards are not yet finalized as long as they seem far from assessing a sought level of safety. In addition, the shortened and hasty assessment of the industrial safety depends solely on what directly endangers mankind security and its economic assets. Moreover, well-known quality standards have not yet established a well-defined code to formulate the safety and liability area of the product quality. Owing to the safety-related weak points mentioned above, the present paper puts forth a unified and applicable mathematical model. Moreover, this paper confirms that humanity's engineering willingness of a prospective industrial product (vehicle) along with its manufacturing plants has not to overlook crucial safety instructions for a multi-entity Environmental Closed System (ECS). The suggested environment-related approach is here checked using three commonly applied methods, namely, SPC, FMEA, and Markov Chains of industrial safety estimation for products /plants. Main findings of the present paper conclude that industrial (product/ plant) safety, in its broadened sense, does embrace the gain/loss statistical data of a product's introductory versions and represents a trade–off function of its profits (resource renovation) and its losses (resources drain). In addition, the comprehensive resource-loss trend helps product designers and concerned researchers meet a wide range of customer requirements and more operational regulations.

Abstract: This paper examines the application of proposed Design Structure Matrix (DSM) by modeling the collaborative design of the Automotive Powertrain System. A task of the whole design process is divided into several levels and some specific design tasks. Respectively, the flow diagram is set up based on the DSM principle. In order to optimize the design process and to shorten the development cycle, detailed analysis and reconstruction of DSM were performed by eliminating iterative design process.

Abstract: The mining production systems, both for underground and open pit extraction consist mainly in a string of equipment starting with the winning equipment (shearer loader, in case of underground longwall mining or bucket wheel excavator in case of open pit mining), hauling equipment (armored face conveyor in longwall mining or the on-board belt conveyor in case of excavators), main conveying equipment (belt conveyor in both cases), transfer devices, stock pile or bunker feeding equipment. This system of mainly serially connected elements is characterized by the throughput (overall amount of bulk coal respectively overburden rock produced), which is dependent on the functioning state of each involved equipment, and is strongly affected also by the process inherent variability due to the randomness of the involved processes (e.g. the cutting properties of the rock). In order to model and simulate such production systems, some probabilistic methods are applied arising from the artificial intelligence approach, involving unit operations and equipment, as the overall system as a whole, namely the Monte Carlo simulation, neural networks, fuzzy systems, and the Load Strength Interference methods. The results obtained are convergent and offer the opportunity for further developments of their application in the study of mining production systems.