Faisal Hasan

Physiological effect of vibrations on tractor drivers under variable ploughing conditions.

Physiological Effect of Vibrations on Tractor Drivers under Variable Ploughing Conditions: Mohammad Muzammil, et al. Department of Mechanical Engineering, Ergonomics Laboratory, Faculty of Engineering & Technology, Aligarh Muslim University, India—The vibration conditions to which tractor operators are subjected are complex and varied with multi axis translation and rotational vibration inputs to different parts of the body. Working under such conditions may lead to human fatigue and other driving related hazards. The present research was carried out to study the operators under varying conditions of vibration while driving a tractor with and without farm equipment on different fields. Test runs were conducted in wet and dry fields to determine the levels of vibration generated at different engine speeds. On the basis of this study three levels of vibration namely 2.5, 3.5 and 5.0 m/s2 were selected. Five subjects, all males, with no experience in the field of tractor driving participated in the study. The data were analyzed on the basis of three factor repeated measure kind of experimental design. The results showed that the main effects of farm equipment and the vibration level were statistically significant but the effect of field type was found to be statistically non‐significant. The results of the study call upon the ergonomists to design and develop a tractor where the driver may be relieved of vibration induced stresses. Front loading of farm equipment is recommended for improved visibility and better working posture.

Neural network model for discharge and water-level prediction for Ramganga River catchment of Ganga Basin, India

ABSTRACT Discharges and water levels are essential components of river hydrodynamics. In unreachable terrains and ungauged locations, it is quite difficult to measure these parameters due to rugged topography. In the present study an artificial neural network model has been developed for the Ramganga River catchment of the Ganga Basin. The modelled network is trained, validated and tested using daily water flow and level data pertaining to 4 years (2010–2013). The network has been optimized using an enumeration technique and a network topology of 4-10-2 with a learning rate set at 0.06, which was found optimum for predicting discharge and water-level values for the considered river. The mean square error values obtained for discharge and water level for the tested data were found to be 0.046 and 0.012, respectively. Thus, monsoon flow patterns can be estimated with an accuracy of about 93.42%. Editor M.C. Acreman; Associate editor E. Gargouri

Human Performance under the Impact of Continuous and Intermittent Noise in a Manual Machining Task

Experimental research was conducted to determine the performance of operators while carrying out industrial tasks in the presence of continuous and intermittent noise. Experimental investigations were carried out at 90, 95, 100 and 105 dB (A) for both types of noise. Two groups of subjects, one having a working experience of 2-7 years and other with 7-12 years were selected for the two studies. The number of units produced was taken as the measure of human performance. The results of the study showed that the level of noise and working experience were statistically significant when the task was carried out in a continuous noise environment. While under intermittent noise conditions effects of noise and work experience and the interaction effect of noise and work experience were all observed to be statistically significant. Investigations also revealed that intermittent noise had a more detrimental effect on performance when compared with continuous noise.

Product family formation based on multiple product similarities for a reconfigurable manufacturing system

The design of a reconfigurable manufacturing system (RMS) revolves around product family which can cater all the variety within a product family and can be subsequently reconfigured to accommodate future products belonging to distinct product families. Keeping in view the high degree of customisation in the product design, it is being required to have modular structure of products to accommodate such customisation. Similarity measures for such modular products have not been considered in the past. The present paper proposed a novel technique for the product family formation in RMS based on multiple product similarities associated with modular products comprising of several parts. These similarities include modularity, reusability and commonality. Modularity is the degree to which a product is composed of autonomous modules; reusability is the ability to use the identical resources in dissimilar configurations without any change while the commonality is the property which is mainly concerned with the grouping of the products. A descriptive mathematical model for the calculation of similarities is presented demonstrated with the help of a numerical example and the similarity values obtained are depicted in the form of a dendrogram and are discussed in the light of some previous related works on the topic.

Genetic Modelling for Selecting Optimal Machine Configurations in Reconfigurable Manufacturing System

Selecting the optimum machine configurations for any product flow line has direct implications on the system performance. In the present paper, an evolutionary algorithm based methodology has been proposed for optimal machine assignment based on a weighted objective function. The objective function includes reliability, cost, production time and operational capability as performance indicators. The methodology demonstrates how several performance parameters can be dealt with, in order to select optimal machine configurations for distinct stages across any serial product flow line. The proposed approach can possibly be employed in handling the RMS performance issues and optimal trade-offs among the various performance parameters.

An approach towards scalability for reconfigurable product flow line through unbalancing

A timely and cost effective response to dynamic market scenario is becoming one of the key factors for the success of manufacturing enterprises. Reconfigurable manufacturing systems are recognised as the next generation manufacturing systems, which are responsive to these market changes. One of the major challenges which need to be addressed for designing and operating such systems include implementing scalability within these systems. In the past, some strategies have been proposed for scalability aspect based on routing flexibility and stage paralleling. In this paper, an approach based on ‘unbalancing’ is proposed as a potential technique for scalability of reconfigurable product flow lines. The proposed approach is based on the fact that productivity variations may be achieved from a flow line by varying the degree of imbalance in mean operation time values at stations on the product line. The proposed approach is demonstrated using a coupled reconfigurable product flow line.

Performance modeling of reconfigurable manufacturing system for different dispatching strategies under exception

A Reconfigurable Manufacturing System (RMS) is having potential for quick adjustment in its production capacity and functionality. These RMSs are considered to be one of the technologies enabling shorter lead times, more product variants, fluctuating volumes of products, shorter product life cycles and lower cost. This paper presents the performance modeling of a hybrid system comprising of dedicated and reconfigurable machine tools simultaneously. The modeling focuses on handling of exceptional situations. One such handling situation arises when there is a breakdown of any resource like machine within the system. The dedicated machines are subjected to random failures and once there is the failure, the jobs are transferred to the reconfigurable machines after suitable reconfiguration to carry out the sequential operation required on the job. Two different production scenarios, first, operation of the system over some predetermined period of time and, secondly, operation of the system for a fixed quantity of products were modeled using ARENA® discrete event simulation software. Three different dispatching strategies for reactive scheduling of parts based on total average waiting time in queue, total downtime of the failed machine and capacity of the buffer in between the machines were analyzed. The performance of the system was analyzed in terms of productivity, congestion and make-span time. Finally, the results were analyzed and were discussed in the light of previous researches carried out on the topic.

Design of a workstation and its evaluation under the influence of noise and illumination for an assembly task

OBJECTIVE An experimental research was conducted to design a workstation for a lock manufacturing assembly. PARTICIPANTS Two experiments were conducted in the present study. Nine male subjects in the age range of 18-35 years participated in the first experiment. For the second experiment, nine subjects in each of the three age groups (viz. 17-22, 23-28 and 29-35 years) volunteered for experimental investigations. METHOD The designed workstation was evaluated under varying levels of noise and illumination for workers of different age groups. Three different workstations were evaluated. The task was performed by a worker in two different sitting positions and three settings of arms position. RESULTS It was found that workstation type, backrest support and arms positions were all having a statistically significant effect on task performance. Workstation with work surface to seat height ratio of 1.82 was found to be better when the task was performed using backrest and arms were supported on the work surface. This workstation was evaluated for three different age groups of workers under different levels of noise and illumination. The results of the study showed that age of the worker, illumination level and level of noise were all contributing significantly towards task performance. CONCLUSIONS The design of a workstation for assembly task would help greatly in creating a better working environment and enhancing the productivity of workers exposed to environmental stressors like noise and illumination.

Part family formation using skip moves and lazy machines in a reconfigurable manufacturing system

With the advent of modern manufacturing systems like RMSs many issues pertaining to its design and implementation has been taken up in the recent past. As per definition, RMS design initiates with the classification of product into part families. Subsequent reconfiguration of the system is carried out to cater new part families. The issue of part family formation in RMS is considered to be of utmost importance for this new manufacturing paradigm, i.e., RMS as the complete philosophy of its design and operation revolves around part families. Thus, it becomes exceeding important that parts must be grouped into logical families based on similarities in manufacturing or design features to physically realise the implementation of RMSs. Though some techniques for such formation for RMSs were proposed in the past but the present technique eliminates some of the shortcoming in those proposed techniques. In the present paper, an operations string-based methodology known as skip moves and lazy machines (SMLM) has been undertaken for part family formation. The paper also discusses on some of the early similarity indices developed using operation sequencing. The technique is demonstrated using a numerical example and the results are finally discussed in light of some previous researches on the topic.

Performance modelling of dispatching strategies under resource failure scenario in reconfigurable manufacturing system

Reconfigurable manufacturing systems are considered to be one of the newer technologies which cannot only meet stochastic product demand but can also produce products having customised variety. The paper presents performance modelling of a reconfigurable manufacturing system equipped with dedicated and reconfigurable machines under the failure of any resource. The dedicated machines are assumed to be subjected to random failures or breakdowns and upon occurrences of such breakdowns or failures, the jobs from these machines are routed or dispatched to reconfigurable machines to carry out the desired operation after suitable reconfiguration. Different dispatching strategies under two production scenarios were simulated using ARENAO discrete event simulation software. Performance of dispatching strategies proposed was analysed in terms of productivity, congestion and make-span time. The results were analysed and were discussed in light of previous researches carried out on the topic.