Mirza Jahanzaib

Cell formation in a cellular manufacturing system using simulation integrated hybrid genetic algorithm

A cell formation problem, which minimizes value added work-in-process (VAWIP).Developed a mathematical model to minimize VAWIP.Developed an algorithm by integrating simulation with genetic algorithm (GA).Simulation integrated hybrid GA (HSGA) is used to solve the model.A case study of auto industry is presented for practical application of the model. Work-in-process (WIP) is an important performance measure of contemporary manufacturing systems such as cellular manufacturing system (CMS). The term value added WIP (VAWIP) is used because; the value of WIP increased at each stage of production due to the application of resources in the form of machines, time and energy. This research is an attempt of cell formation (CF) in CMS that would minimize the value added work in process. To achieve this objective a mathematical model is formulated and solved using discrete event simulation (DES) integrated hybrid genetic algorithm (SHGA) in which simulation and the genetic algorithm have been integrated to form an approach called SHGA and it has the advantages of using both. The proposed approach has been applied on local automobile part supply industry for cell formation. While solving problem with SHGA each population has been evaluated using the discrete event simulation (DES). The solution was found in the form of assigning machines to cells in a way that resulted in minimum value added work in process. A 8.55% reduction of value added work in process occurred using SHGA. The reduction of value added work in process VAWIP in the system resulted in the reduced waiting and throughput times, whereas increased throughput rate and machine utilization.

Modeling of cutting speed (CS) for HSLA steel in wire electrical discharge machining (WEDM) using moly wire

Abstract The high capital costs of wire electrical discharge machining (WEDM) equipment necessitate optimal utilization of the WEDM process and equipment. Cutting speed (CS) is a key performance measure to achieve this objective. However, process parameters of WEDM greatly hamper CS and hence productivity and machining efficiency. It is therefore essential to pick the right combination of parameters to attain better CSs. In this paper, five process parameters which include pulse on-time, pulse off-time, pulse frequency, power, and wire speed were used to develop an empirical relationship between process parameters and CS. A regression model based on experimental data was developed and validated through confirmation tests. Experiments have been conducted on high-strength low-alloy steel using molybdenum wire. Analysis of variance was applied to segregate significant process parameters and it was revealed that pulse off-time, power, and pulse frequency were the major parameters affecting CS. Contour plots have been established to select the best process parameters in addition to the developed model. Stability of moly wire was also explored using scanning electron microscope and energy dispersive spectroscopy analysis. Results showed that moly wire retains its original surface quality and dimensions which contributes to dimensional accuracy of parts.

Integration of cell formation and job sequencing to minimize energy consumption with minimum make-span

Cell formation is the fundamental step while designing a cellular manufacturing system. Integration of job sequencing with cell formation can attain lower make-spans. The traditional cell formation and scheduling problems consider performance indicators such as productivity, time and flexibility in cellular manufacturing system; however, energy consumption has not been given due attention. Therefore, this research addressed the minimization of total energy consumption by implementing an energy-efficient schedule at the cell formation stage of cellular manufacturing system. For this purpose, a two-phase approach is proposed; in phase I, formation of independent cells is being carried out by considering energy-efficient routings and genetic algorithm is used for improving search performance. In phase II, a formulation is being developed to compute the total energy of the system based on optimal job sequence with respect to minimum idle running of the machines in each independent cell. For the proposed approach, a code is being developed in MATLAB software. Different sample problems have been evaluated. The results showed that the proposed approach is effective in generating independent cells and sequences with minimum energy consumption and make-span.

An Empirical Analysis of a Process Industry to Explore the Accident Causation Factors: A Case Study of a Textile Mill in Pakistan

Industrial revolutions not only improved the general lifestyle of individuals but also brought an increase in the diversity of the manufactured goods. This diversification involved use of advanced technology and complex methods that entailed dangerous conditions. According to international labor organization, occupational accidents cause death of more than two million individuals each year in different industries. Process industries are complex in nature and tend to lead to more accidents. In Pakistan among the process industries, textile mills are the most accident prone industries in recent times. Therefore, an empirical analysis of a textile process industry has been done using structural equation modelling to examine the interactions between the contributory factors of accidents. Results revealed that unsafe acts are a major contributor to human error, equipment error and unsafe environment that in turn lead to the calamities and disasters that can be avoided with proper safety measures in place.

Prioritizing Factors of Entrepreneurial University to Inculcate Enterprise Formation Pursuit Among University Graduates Using Analytical Hierarchical Process

The objective of this paper is to prioritize entrepreneurial activities in higher education institutions to inculcate enterprise development pursuit among university graduates. Various phases of enterprise development process are determined along with prominent activities of entrepreneurial universities through literature review. Problem formulation is done by structuring goal, objectives and alternatives into a hierarchical model in order to prioritize factors with the help of Analytical Hierarchical Process (AHP). Experts of academic entrepreneurship are approached for pairwise comparison of factors on the preference scale of nine levels with the help of software tool Expert Choice 11. After recording judgments, preferences of all experts are combined in order to get overall priorities of objectives and alternatives. Results show that Internal Motivation has highest and Business Growth and Sustainability have lowest priority along with priorities of all other objectives of enterprise formation process falling between both. Moreover, University Incubation Center is prioritized among alternatives in order to achieve objectives. Sensitivity analysis of results is carried out with the help of Expert Choice in which weight of a single objective is varied to observe effect on hierarchical model. Research presents a complete picture to academicians and policy makers to determine role of universities for entrepreneurship development in country. It will also help government officials to allocate resources in a prioritized way in order to achieve specific objectives.

Impact of Project Complexity and Environmental Factors on Project Success: A Case of Oil and Gas Sector of Pakistan

Oil and gas industry significantly contribute for economic development of countries enriched with petroleum resources. Mega projects of oil and gas sector usually face many challenges due to environmental issues, high level of risks, huge investments, tight schedules and interdependencies between project activities. Therefore keeping in view, the issues faced by oil and gas sector this study was made to analyze the impact of project complexity and environmental factors on success of oil and gas projects of Pakistan. Based upon hypothetical framework developed for this study, data collection was made from an oil and gas company of Pakistan. After which, data analysis was carried out by using a statistical technique known as structural equation modeling. Project complexity, environmental factors and project success were taken as constructs for model evaluation on AMOS. Analysis of data has concluded that project complexity has negative impact on project success whereas better control over environmental factors enhance the project success rate.

Continuous Quality Improvement (CQI) framework: A case of industrial engineering department

This paper aims to present an educational framework for outcomes based continuous quality improvement. Well defined program outcomes, program educational objectives and assessment process have been developed to ensure graduates’ outcomes achievement. Direct and indirect tools have been used for assessment process. Course evaluation surveys, alumni surveys, and employer surveys have been deployed for indirect outcome assessment. Exams, quizzes, assignments and projects, on the other hand, have been used for direct outcome assessment. In developed framework, the educational processes committees and facilities committees have been integrated to continuously evaluate and monitor the educational processes. Furthermore, program outcomes and course learning outcomes are proposed to be evaluated and continuously monitored by programs goals committee and continuous course improvement committee respectively. Forms and procedures have been developed to assess student outcomes.