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Purpose This paper aims to accomplish friction stir welding (FSW) of Al–Li alloy AA8090 to determine optimal settings of the process parameters for higher tensile strength and higher micro-hardness (MH) to achieve the objective of adequate butt-joint strength. Design/methodology/approach An empirical relation is implemented to govern the utmost influence parameters, i.e. tool rotation speed (TRS), tool transverse speed (TTS) and dwell time (DT). Taguchi grey relational analysis (GRA) was applied for multi-response optimization of response parameters. The grey relational grades (GRs) have been calculated for both the responses MH and ultimate tensile strength to get optimal parametric settings. The variance test has been performed to check the adequacy of the model. Findings The Taguchi L9 orthogonal array design was used in establishing the relation between input parameter and output parameter (tensile and MH). TTS and DT have been predicted to be the two most important parameters that influence the extreme quality features of joints by using friction stir welding. Scanning electron microscopy fractography shows the ductile failure of the welded joints. Originality/value The experimental trials provided the followings results, maximum ultimate tensile strength (UTS) of 219 MPa and MH 107.1 HV under 1,400 rpm of TRS, 40 mm/min of TTS and 8 s of DT founded the optimum value through GRA.

Purpose Milling is a flexible creation process for the manufacturing of dies and aeronautical parts. While machining thin-walled parts, heat generation during machining essentially affects the accuracy. The workpiece temperature (WT), as well as the responses like material removal rate (MRR) and surface roughness (SR) for input parameters like cutting speed (CS), feed rate (F), depth-of-cut (DOC), step over (SO) and tool diameter (TD), becomes critical for sustaining the accuracy of the thin walls. Design/methodology/approach Response surface methodology was used to make 46 tests. To convert the multi-character problem into a single-character problem, the weightage was assessed using the entropy approach and the grey relational coefficient (GRC) was determined. To investigate the connection among input parameters and single-objective (GRC), a fuzzy mathematical modelling technique was used. The optimal performance of process parameters was estimated by grey relational entropy grade (GREG)-fuzzy and genetic algorithm (GA) optimization. Findings SR was found to be a significant process parameter, with CS, feed and DOC, respectively. Similarly, F, DOC and TD were found to be significant process parameters with MRR, respectively, and F, DOC, SO and TD were found to be significant process parameters with WT, respectively. GREG-fuzzy-GA found more suitable for minimizing the WT with the constraint s of SR and MRR and provide maximum desirability of 0.665. The projected and experimental values have a good agreement, with a standard error of 5.85%, and so the responses predicted by the suggested method are better optimized. Originality/value The GREG-fuzzy-GA is a new hybrid technique for analysing Inconel625 behaviour during machining in a 2.5D milling process.

Single point incremental sheet metal forming has passed through a period of ample improvement with developing responsiveness from research societies and industries globally. The process has expressively spared the practice of using costly dies, which makes it an appropriate process for manufacturing prototypes and small batch production. It also discovers easiness in fabricating components of timeworn equipment. Additionally, in recent years, aluminum alloys become the most commonly used materials in the automotive, aeronautics, and transportation industries for their structural and other applications. The effect of various process parameters on the formability of Single Point Incremental Forming of aluminum alloys has been critically surveyed. Ultimately, this article also debated the dares associated with the Single Point Incremental Forming process and recommended some correlated research regions which probably charm significant research considerations in the future.

Purpose This paper aims to predict the performance of friction stir welded AA8090 joint. Design/methodology/approach In the present study, Al-Li AA8090 plates are butt joined using friction stir welding (FSW). The experiments are designed and optimized using a Taguchi-orthogonal array. The experiments are conducted at three different process parameters, i.e. tool rotational speed (TRS), tool transverse speed (TTS) and dwell time (DT). The ultimate tensile strength (UTS) and microhardness (MH) are considered as response parameters. In addition, a statistical tool (ANOVA) is used to check the adequacy of experiment results. Findings The maximum UTS of 220 MPa is obtained at a TRS of 1,400 rpm, tool TTS of 40 mm/min and DT of 15 s. The maximum microhardness is obtained for 1,400 rpm, 25 mm/min and 8 s, i.e. 108.6 HV. The microstructural showed that the minimum grain is observed at the nugget zone. Fractography analysis revealed the ductile behaviour of fractured surfaces. Originality/value From the reported literature, it has been observed that very limited work is reported on the FSW of AA8090 alloy. Further, the thermal behaviour of welded joint is also observed in this experimental work.

The single-point incremental forming has been globally accepted as an advanced method of sheet metal forming due to its rapid prototyping and economic benefits. The process has sensitively released the practice of using expensive dies, making it suitable for manufacturing custom-built products in tiny batches. Further, it is getting acceptance in producing parts of shabby machinery. In recent years, superalloys have become the most commonly used materials in the transportation, automotive, aeronautics and marine industries due to their fundamental and structural applications. The input parameters considered in this study are step size, feed rate and tool spindle speed. The effects of all three process parameters on the geometrical accuracy of Inconel 625 superalloy conical parts formed by the single-point incremental forming process are considered in this work. The deviations in roundness, concentricity, half-cone angle and straightness from the target values were considered as response parameters to measure the accuracy. The results showed that the part accuracy could be enhanced by using minimum step size, feed rate and maximum tool spindle speed.

Pressure die-casting is generally useful in casting of zinc, Aluminium, magnesium, lead and tin-based alloys. Better surface finish, tolerances and dimensional accuracy can be achieved by optimization of significant process parameters of Pressure die casting (PDC) such as solidifying-time, melting-temperature, fill-up-time, inoculation-pressure and plunger-velocity etc. In addition, with the proper selection of optimum process parameters the PDC defects such as flash, cold-shut, porosity, misrun, etc. also minimized. In the present work, minimization of the PDC defects using artificial intelligent technique comprises of Genetic-algorithm (GA) and fuzzy-logic-methodology (FLM). A380: A silicon based aluminium alloy carburetor-housing is considered for the same. L18 orthogonal array based Taguchi design approach is considered for number of % defects per batch in a lot of 500 components as FLM knowledge base. To estimate the extent of accuracy of predictions made by FLM, regression analysis isperformed. FLM is also validated with R-square approach. Besides this, ANOVA has also been applied to estimate the significance level in terms of percent contribution among the input parameters and defects during PDC. Solidifying-time & fill-up-time has been found most sensitive parameter. Melting-temperature, plunger-velocity and inoculation-pressure are also identified as influencing parameters with comparatively low percent contribution. To optimize process parameters GA is applied and the fitness value is calculated using FLM. From this combination of artificial intelligent approach an optimum combination of process parameter has been obtained. Further, the results are compared with the Taguchi methodology and the approach provides appreciable amount of decrease in PDC-defects by fine tuning the input parameter.

In the current research, rotary ultrasonic machining was used to drill holes in quartz material. The effect of different RUM parameters namely tool feed rate, tool rotational speed and ultrasonic power on material removal rate and surface roughness has been studied experimentally. The response surface methodology with central composite design has been used to design the experiments. From the desirability approach, the optimum setting of the rotary ultrasonic machining parameters was found to be the tool rotational speed of 4968 rpm, feed rate of 0.55 mm/min, and ultrasonic power of 80% for achieving the maximum MRR of 0.2135 mm3/s and minimum SR of 0.3685 μm. Microstructure analysis of the machined surface was performed by using scanning electron microscopy in order to study the mechanisms of material removal under the different settings of RUM parameters. It was observed that at very low feed (0.08 mm/min) and high rpm (5681) the material is predominantly removed by plastic deformation whereas at high feed (0.92 mm/min) and low rpm (2318) the material is removed by brittle fracture.

A bell crank lever is mainly defined as a type of lever which is utilized to change the direction of motion either through 90° or 180°. A bell crank lever is subjected to large amount of stresses, so they are important components in terms of safety. In the present study, 3D models of a bell crank lever are prepared in the SOLIDWORKS, then boundary conditions are applied, and model is analyzed in ANSYS. The stress obtained is compared with the analytical stress. The FEA and analytical result are found to be in close agreement. Further, the different cross sections of same area models are prepared in SOLIDWORKS and analyzed in ANSYS. The stresses obtained are compared, and the cross section with least stress is chosen for optimization of design parameters.

Rotary ultrasonic machining has the capability to process the materials which are very hard, brittle and electrically non-conductive, with efficiency and cost-effectiveness. The current investigation is focused on the use of Taguchi-Grey relational analysis to improve the machining performance of Rotary ultrasonically machined quartz glass. Ideal machining parameters were calculated by grey relational grade calculated in grey relational analysis which was designed for simultaneous optimization of material removal rate and surface roughness. The rotary ultrasonic machining parameters setting with tool rotational speed of 5000 rpm, tool feedrate of 0.75 mm/min, and ultrasonic power of 55% were found to have the highest grey relation grade resulting in the high material removal rate and low surface roughness of the processed material. The tool feed rate was found to be the most critical parameter followed by ultrasonic power and tool rotational speed on the rotary ultrasonic machining characteristics. Confirmatory experiments were also executed to authenticate the forecasted results obtained from the Taguchi-Grey relational analysis. Furthermore, the microstructural investigation was carried out to comprehend the mechanism of material removal in the rotary ultrasonic machining of quartz glass at optimum parameter setting. It was found that the material was removed in the brittle mode and abrasion during the machining at optimum parameter setting. The sharp cutting edges of the diamond grits have caused the abrasive wear and brittle fracture of the quartz material. The interlinking of the cracks results in the pullout of the grains and consequently deeper grooves are formed on the machined surface.

Scheduling problems in an FMS have been considered as complex optimization problems whose solution by conventional techniques requires a great deal of efforts and time. In this paper, a simultaneous loading and scheduling of part and tool has been proposed for a flexible manufacturing system which has identical machines and a common tool magazine. All the tools are stored in the common tool magazine, and shared among the different machines through a material handling system. Each tool type is single in number. A modified genetic algorithm (MGA) with three parent crossover and a mutation operator is used to find the optimal solution of the loading and scheduling problem. The MGA uses an algorithm which is based on Giffler and Thompson procedure with a heuristic approach to resolve the job conflict and generate an active feasible schedule. The performance of the proposed algorithm is analyzed by comparing the makespan results with the results existing in literature. It is observed that the MGA yields better results than the algorithms reported so far. Furthermore, efficiency of MGA improves as the problem size increases.

The investigation on the fractured surface of steel wires in the tensile test and torsion test has been carried out using stereomicroscopic technique. The analysis has been done on cold drawn wires subjected to different pass schedules. Investigation revealed that pass schedule having optimum true strain resulted in the best mechanical properties. Hot rolled piano wire rod having carbon percentage 0.87% has been used in the investigation. The fully pearlitic microstructure is developed during lead patenting process of wire rod at 950 ℃. The wire rod has been reduced from 7.00 mm diameter to 2.6 mm wire diameter by subjecting it to three different pass schedules. The investigation revealed that highest UTS and TS properties are achieved in pass schedule-1 and pass schedule-2 respectively in the cold drawn wire of diameter 2.60 mm. The high reduction rate per die in pass schedule-1 has a negative effect on torsion strength whereas the low reduction rate per die in pass schedule-3 has negative effect on torsion strength as well as tensile strength.

Environmental protection and sustainability issues in food sector have attracted global concerns in the past two decades. Companies and government in many countries have started realizing the importance of greening their supply chains. Green supply chain management has gained special attention of public and many companies are now interested in adopting it as their strategy to advance their brand image, capturing more market share and to win the trust of the customer. The purpose of this paper is to explore the diverse performance indicators and sub-indicators responsible for green supply chain management implementation and to check its reliability and to rank them using analytic hierarchy process analysis. After extensive literature review and consulting Industrial experts, the study has suggested 13 performance indicators and 79 sub-indicators. The quantitative phase was conducted through a survey using standard questionnaire with various agro based companies followed by a qualitative phase, where the duly filled questionnaires were received, edited and further analyzed. It has been concluded that internal environmental management, environmental design and regulatory pressure are ranked as the top three performance indicators. The sensitivity analysis has also been performed to see the effect of weightage on the final ranking of performance indicators. This is one of the first studies that suggest the performance indicators for implementation of green supply chain management in agro industry. The study will certainly aid the related organizations to implement green supply chain management.

This work analyses the right hand anthropometric dimensions of 1540 male industrial workers of the age ranging from 18 to 62 years belonging to four different divisions of Haryana state of India. Hand index derived from measured hand dimensions can be used to estimate differences related to sex, age and race in forensic and legal sciences. It has been calculated as percentage of hand breadth over the hand length; which suggests that the male industrial workers population of state belong to mesocheir group of hands. The hand length, breadth and derived index of the subjects have been compared with population of the twelve other states of the country. Comparison of hand length, hand breadth and hand index of the subjects of the state has also been made with the male population of twenty-five other countries. There exist significant differences in hand anthropometric –amongst male population of different countries and also within country - which must be taken into consideration while designing the hand tools or equipment to be controlled by users’ hands of different populations.Keywords: Hand length, hand breadth, hand index, population identification

The present work deals with the optimal placement of piezoelectric actuators on a thin plate using modified control matrix and singular value decomposition (MCSVD) approach. The MCSVD is considered as the fitness function and optimal positions of the actuators are obtained by maximizing it with MHGA (modified heuristic genetic algorithm). Vibration suppression has been studied for simply supported plate with piezoelectric patches in optimal positions to suppress first specified modes using LQR (linear quadratic regulator) controller. It is observed that the positions of patches obtained with this approach give greater vibration suppression, reduced computational requirements, and provide global optimum solution only.

Performance of neural networks depends upon several input parameters. Several attempts have been made for optimization of neural network parameters using Taguchi methodology for achieving single objective such as computation effort, computation time, etc. Determination of optimum setting to these parameters still remains a difficult task. Trial-and-error method is one of the frequently used approaches to determine the optimal choice of these parameters. Keeping in view the problems with trial-and-error method, a systematic approach is required to find the optimum value of different parameters of neural network. In the present work, three most important distinct performance measures such as mean square error between actual and prediction, number of iteration, and total training time consumption have been probably considered first time concurrently. The multiobjective problem has been solved using Grey–Taguchi methodology. In this study, optimal combinations of different neural network parameters have been identified by using the Taguchi-based Grey relational analysis. The data set includes 81 sets of milling data corresponding to three-level full factorial experimental design for four cutting parameters, i.e. cutting speed, feed, axial depth of cut, and radial depth of cut, respectively. The output is average surface roughness for the experiment. The performance of different neural network models has been tabulated in L36 orthogonal array. Confidence interval has also been estimated for 95% consistency level to validate the optimum level of different parameters. It was found that the Taguchi-based Grey relational analysis approach can effectively be used as a structured method to optimize the neural network parameters settings, which can be easily implemented to enhance the performance of the neural network model with a relatively small size and time saving experiment. The result clearly indicates that the optimal combination of neural network parameters obtained by using the proposed approach performs better in terms of low mean square error, small number of iterations, and lesser training time required to perform the analysis which further results in lesser computation effort and processing time. Methodology proposed in this work can be utilized for any type of neural network application to find the optimum levels of different parameters.

Scheduling of part and tools without considering material handling devices may result into non-implementable results as the material handling system constraints affect the overall scheduling. In this paper, an attempt has been made for the simultaneous scheduling of part, tool and two automated guided vehicles (AGVs) in a flexible manufacturing system which has identical machines with no on-board tool magazine. All the tools are stored in a common tool magazine and are shared among different machines through a material handling system. Each tool type is single in number. The problem has two interrelated problems; one as loading and scheduling of part and tool and other as scheduling of AGVs. Two heuristics namely priority dispatching rules (PDRs) and modified genetic algorithm (MGA) with three parent crossover are used to find the optimal solution to the integrated scheduling problem. Both PDRs and MGA use an algorithm based on the concept of Giffler and Thompson procedure and a heuristic approach to generate the active feasible schedule. The performance of the two proposed algorithm is compared for the results of makespan. It was found that the MGA gives better results.

PurposeIn order to achieve excellence in manufacturing, goals like lean, economic and quality production with enhanced productivity play a crucial role in this competitive environment. It also necessitates major improvements in generally three primary technical areas: variation reduction, equipment reliability, and production scheduling. Complexity of the real world scheduling problems also increases with interactive multiple decision‐making criteria. This paper aims to deal with multi‐objective flow shop scheduling problems, including sequence dependent set up time (SDST). The paper also aims to consider the objective of minimizing the weighted sum of total weighted tardiness, total weighted earliness and makespan simultaneously. It proposes a new heuristic‐based hybrid simulated annealing (HSA) for near optimal solutions in a reasonable time.Design/methodology/approachSix modified NEH's based HSA algorithms are proposed for efficient scheduling of jobs in a multi‐objective SDST flow shop. Problems of up to 200 jobs and 20 machines are tested by the proposed HSA and a defined relative percentage improvement index is used for analysis and comparison of different MNEH's based hybrid simulated annealing algorithms.FindingsFrom the results, it has been derived that performance of SA_EWDD (NEH) up to ten machines' problems, and SA_EPWDD (NEH) up to 20 machines' problems, were better over others especially for large sized SDST flow shop scheduling problems for the considered multi‐objective fitness function.Originality/valueHSA and multi‐objective decision making proposed in the present work is a modified approach in the area of SDST flow shop scheduling.

The present work deals with the optimal placement of piezoelectric actuators on a thin plate using Modified Control Matrix and Singular Value Decomposition (MCSVD) approach. The problem has been formulated using the finite element method using ten piezoelectric actuators on simply supported plate to suppress first six modes. The sizes of ten actuators are combined to outline one actuator by adding the ten columns of control matrix to form a column matrix. The singular value of column control matrix is considered as the fitness function and optimal positions of the actuators are obtained by maximizing it with GA. Vibration suppression has been studied for simply supported plate with piezoelectric patches in optimal positions using Linear Quadratic regulator) scheme. It is observed that MCSVD approach has given the position of patches adjacent to each-other, symmetric to the centre axis and given greater vibration suppression than other previously published results on SVD.&nbsp

The present work considers with the optimal placement of piezoelectric actuators on a thin plate via modified control matrix and singular value decomposition (MCSVD) approach using Modified Heuristic Genetic Algorithm (MHGA). Optimal placement of piezoelectric actuators is investigated to suppress the first six modes on cantilever plate. Vibration suppression has been studied for cantilever plate with piezoelectric patches in optimal positions using LQR (Linear Quadratic regulator) scheme. It is observed that developed present approach has given the greater closed loop damping ratio and lesser computational requirements.

A multiobjective optimization procedure is proposed to deal with the optimal number and locations of collocated/noncollocated sensors and actuators and determination of LQR controller gain simultaneously using hybrid multiobjective genetic algorithm-artificial neural network (GA-ANN). Multiobjective optimization problem has been formulated using trade-off objective functions ensuring good observability/controllability of the structure while minimizing the spillover effect and maximizing closed loop average damping ratio. Artificial neural networks (ANNs) are used to train the input as varying numbers and placements of sensors and actuators and the outputs are taken as the three objective functions (i.e., controllability, observability, and closed loop average damping ratio), thus forming three ANN models. The trained mathematical models of ANN are fed into the multiobjective GA. The hybrid multiobjective GA-ANN maintains the trade-off among the three objective functions. The ANN3 model is used experimentally to provide the control inputs to the piezoactuators. It is shown that the proposed method is effective in ascertaining the optimal number and placement of actuators and sensors with consideration of controllability, observability, and spillover prevention such that the performance on dynamic responses is also satisfied. It is also observed that damping ratio obtained with hybrid multiobjective GA-ANN and found with ANN experimentally/online holds well in agreement.

The present work analyses different parameters of pressure die casting to minimize the casting defects. Pressure diecasting is usually applied for casting of aluminium alloys. Good surface finish with required tolerances and dimensional accuracy can be achieved by optimization of controllable process parameters such as solidification time, molten temperature, filling time, injection pressure and plunger velocity. Moreover, by selection of optimum process parameters the pressure die casting defects such as porosity, insufficient spread of molten material, flash etc. are also minimized. Therefore, a pressure die casting component, carburetor housing of aluminium alloy (Al2Si2O5) has been considered. The effects of selected process parameters on casting defects and subsequent setting of parameters with the levels have been accomplished by Taguchi-s parameter design approach. The experiments have been performed as per the combination of levels of different process parameters suggested by L18 orthogonal array. Analyses of variance have been performed for mean and signal-to-noise ratio to estimate the percent contribution of different process parameters. Confidence interval has also been estimated for 95% consistency level and three conformational experiments have been performed to validate the optimum level of different parameters. Overall 2.352% reduction in defects has been observed with the help of suggested optimum process parameters., {"references":["Anastasiou, K. S., \"Optimization of the aluminium die casting process\nbased on the Taguchi method.\" Journal of engineering manufacture.\nVol. 216, No.7, pp 969 - 977, 2002.","Barua, P. B., Kumar P., Gaindhar J. L., \"Surface roughness optimization\nof V-process casting through casting method, AFS transition. Vol. 45,\npp. 733-768, 1997.","Byne, D. M., Taguchi, T., \"The taguchi approach to parameter design,\nquality progress, pp. 19-26, 1987.","Cowie, J. G., Peters, D. T., Brush, E. F. and Midson, S. P., \"Materials &\nModifications to Die Cast the Copper Conductors of the Induction\nMotor Rotor\" Die Casting Engineer. Pp. 38-46, 2001.","Guharaja, S., Noorul, H. A, Karuppannan, K. M, \"Optimization of green\nsand casting process parameters by using Taguchi-s method.\"\nInternational Journal of Advance Manufacturing Technology. Vol. 30,\nNo. 11, pp. 1040 - 1048, 2006.","Janudom, S., Rattanochaikul, T., Burapa, R., Wisutmethangoon S., and\nWannasin J., \"Feasibility of semi-solid die casting of ADC12\naluminum alloy.\" Transaction of Nonferrous Metal Society of China.\nVol. 20, No. 9, pp. 1756- 1762, 2010.","Noorul, H. A., Guharaja, S. and. Karuppannan K. M. \"Parameter\noptimization of CO2 casting process by using Taguchi method.\"\nInternational Journal Interactive Design and Manufacturing. Vol. 3,\nNo.1, pp. 41-50, 2009.","Oktem, H., Erzurumlu, T. and Col, M. A. study of the Taguchi\noptimization method for surface roughness in finish milling of mold\nsurfaces. International. Journal Advance Manufacturing Technology.\nVol. 28, pp. 694-700, 2006.","Ross, P.J. \"Taguchi Techniques for Quality Engineering.\" McGraw-\nHill Book, New York 1988.\n[10] Syrcos, G. P. \"Die casting process optimization using Taguchi method.\"\nJournal of Material Processing Technology, Vol. 135, pp. 68-74,\n2003.\n[11] Taguchi, G. \"Introduction to Quality Engineering.\" Asian Productivity\nOrganization, Tokyo, Japan 1986.\n[12] Tsoukalas, V. D., Mavrommatis, S. A., Orfanoudakis, N. G. and\nBaldoukas A. K.- \"A study of porosity formation in pressure die casting\nusing the Taguchi approach.\" Journal of Material science and\nengineering\" Vol. 218, No. 1, pp. 77-86, 2004.\n[13] Yang, J. L. and Chen, J. C., \"A Systematic Approach for Identifying\nOptimum Surface Roughness Performance in End-Milling Operations.\"\nJournal of Industrial Technology. Vol. 17, No.2, pp. 2-8, 2001."]}

Minimization of non-productive time of tool during machining for 2.5 D milling significantly reduces the machining cost. The tool gets retracted and repositioned several times in multi pocket jobs during rough machining which consumes 15 to 30% of total machining time depending on the complexity of job. The automatic CNC program commonly generates contour parallel tool path. Optimization of tool path length during on-productive time can be modeled on Traveling Salesman Problem (TSP) which belongs to family of non-deterministic polynomial (NP) hard problem. In the present work, a Hybrid Genetic Algorithm (HGA) has been proposed to optimize the non-productive tool path in which the initial seed solution is generated by special heuristic and combined with random initial solution generated by simple genetic algorithm (SGA). A defined performance index known as Relative percentage deviation (RPD) has been used for analyzing the results by varying the size of the jobs. From the analysis, it is found that HGA shows superiority over SGA for same computation time limit as the stopping criteria.

Bi-criteria flow shop scheduling problems with sequence dependent set up time (SDST) have seen an increasing attention of managers and researchers in recent years. A very restricted research has been reported on bi-criteria SDST flow shop scheduling problems dealing with due date related performance measures. In the present work, a modified heuristic based genetic algorithm (MHGA) has been developed for the aforesaid scheduling problem subject to the minimization of weighted sum of total weighted squared tardiness and makespan criterion. The modified heuristic algorithms, along with other available heuristics and dispatching rules in the literature have also being developed to solve the problem instances given by Taillard. A computational analysis has been made to evaluate the performance of the proposed MHGA for upto 200 jobs and 20 machines problems. Comparative analysis with the help of defined performance index known as relative percentage deviation (RPD) verifies that it is viable and effective approach when compared with others heuristic/dispatching rules based genetic algorithms for the SDST flow shop scheduling, especially for larger sized problems. Keywords: Flow shop scheduling, Modified Heuristic Genetic algorithm (MHGA), Sequence dependent set up time, makespan, total weighted squared tardiness.

Noise has adverse effect on human health and comfort. Noise not only cause hearing impairment, but it also acts as a causal factor for stress and raising systolic pressure. Additionally it can be a causal factor in work accidents, both by marking hazards and warning signals and by impeding concentration. Industry workers also suffer psychological and physical stress as well as hearing loss due to industrial noise. This paper proposes an approach to enable engineers to point out quantitatively the noisiest source for modification, while multiple machines are operating simultaneously. The model with the point source and spherical radiation in a free field was adopted to formulate the problem. The procedure works very well in ideal cases (point source and free field). However, most of the industrial noise problems are complicated by the fact that the noise is confined in a room. Reflections from the walls, floor, ceiling, and equipment in a room create a reverberant sound field that alters the sound wave characteristics from those for the free field. So the model was validated for relatively low absorption room at NIT Kurukshetra Central Workshop. The results of validation pointed out that the estimated sound power of noise sources under simultaneous conditions were on lower side, within the error limits 3.56 - 6.35 %. Thus suggesting the use of this methodology for practical implementation in industry. To demonstrate the application of the above analytical procedure for estimating the sound power of noise sources under simultaneous operating conditions, a manufacturing facility (Railway Workshop at Yamunanagar, India) having five sound sources (machines) on its workshop floor is considered in this study. The findings of the case study had identified the two most effective candidates (noise sources) for noise control in the Railway Workshop Yamunanagar, India. The study suggests that the modification in the design and/or replacement of these two identified noisiest sources (machine) would be necessary so as to achieve an effective reduction in noise levels. Further, the estimated data allows engineers to better understand the noise situations of the workplace and to revise the map when changes occur in noise level due to a workplace re-layout.

A survey has been conducted to create a database of hand anthropometric dimensions of 878 male industrial workers from medium and small enterprises of Haryana state of India. A set of selected 37 right-hand anthropometric dimensions are measured using the techniques as per the guidelines in NASA – 1024 (1978). This database will be useful for new designs/design modifications of hand tools, workstations, hand apparel, protective equipments, etc. The primary data collected in the study have been used to compute minimum, maximum, mean, standard deviation (SD), coefficient of variation, standard error of mean and different percentile values of all the measured dimensions using SPSS-16 software package. The anthropometric dimensions of the subjects of this state have been compared with the population of the other states of India. The comparison of mean and SD values of hand anthropometric dimensions of the subjects of the state with other adult male population of Jordan, Mexico, Vietnam and Bangladesh has also been made.

A survey was conducted to collect anthropometric dimensions of male industrial workers of northern region of India in the age group of 20-60 years. About 32 anthropometric dimensions were measured of 400 and 83 male industrial workers from different states of the northern region of the country. Range, mean, Standard Deviation (SD), Coefficient of Variation (CV), 5th, 95th, 99th percentile values and E1, E2 ratios for each anthropometric dimension were calculated and compared with those of the other regions of India. The anthropometric data presented constitute the first anthropometric database of industrial workers of northern region of the country. Most of the measurements of the subjects of this region are found higher than those of any other regions of the country indicating a unique and distinct anthropometry of the region, therefore, there is a need for refining the design of existing equipments based on ergonomic considerations before introducing them into this region of the country. The anthropometric dimensions of the subjects of this region were also compared with British, American, Chinese, Japanese, Taiwanese, Polish, Dutch, Filipino, Portuguese and Korean population.

Air pollution in Delhi is a serious environmental problem. In this paper, the effects of meteorological conditions on local air quality are quantitatively assessed by determining the relationships between concentrations of Suspended Particulate Matter (SPM), Respirable Suspended Particulate Matter (RSPM), sulphur dioxide (SO2) and nitrogen dioxide (NO2) with meteorological parameters on monthly basis, from 2000 to 2006. The multi-linear regression approach, used in the study, has facilitated analysis of the air quality-meteorology relationship and predicted the concentrations of SPM and RSPM within a scatter of ±18% and of SO2 and NO2 within a scatter of ±14%.