Safwan Altarazi

A statistical study employing agent-based modeling to estimate the effects of different warehouse parameters on the distance traveled in warehouses

Abstract In manually operated warehouses, the travel distance of the order picker has profound effects on the warehouse cost and efficiency. Estimating this distance is difficult because the warehouse environment is a stochastic one, affected by a great number of parameters. Therefore, we present a comprehensive statistical study to assess how the different warehouse parameters and their interactions affect the travel distance. To estimate the travel distance, we simulate the different designs using agent-based modeling (ABM). Having 324 different designs, ABM has enabled us to build one computer model to simulate all the cases. The study shows that having one cross aisle only and using a class-based storage policy decreases the travel distance. Moreover, the results obtained show that choosing the best routing policy depends on the warehouse layout, which proves the importance of considering the interactions among the different parameters.

Process parameters optimization for multiple-inputs-multiple-outputs pulsed green laser welding via response surface methodology

This study aims to optimally set the operational parameters of pulsed green laser welding with copper. Multi input parameters and critical-to-quality outputs were considered. The chosen inputs were power, pulse duration and pressured air flow, while the outputs were the maximum force handled by the welding joint and the penetration level of the laser weld. Design and analyses for single-response and two-response optimization were presented using response surface methodology, Analysis of variance (ANOVA), and overlaid contour plots. The results indicated that power and pulse duration have the most significant effect on both the maximum force handled and the penetration level. Air flow showed little to no effect on the force handled and critical effect on the penetration level.

Concurrent manual-order-picking warehouse design: a simulation-based design of experiments approach

The design of manual-order-picking warehouses is a combination of interdependent decisions with enormous possible varieties in design components. The strong interrelationship between these components, in addition to the dynamic and interconnected stochastic nature of the problem; necessitate the utilisation of a simultaneous simulation-based approach. This study proposes a concurrent simulation-based design of experiments approach for the design of manual-order-picking warehouses. The proposed approach can investigate all possible warehousing design combinations with their stochastic nature and interactions; hence, widening the search for performance improvement. The examined design components include warehouse throughput, size, layout, operational policies and manpower/carts. Furthermore, the presented approach captures the probabilistic nature of all the key warehouse functions of receiving, unloading, put away, storage, preparation and picking and shipping; and evaluates the performance of the studied designs using the cycle time for a stock keeping unit in the warehouse. Statistical analysis of the simulation results showed several interesting findings; horizontal layout was preferable over all other types of layouts and small size warehouses perform better than other large sizes. The study has also recommended using high throughput for traditional layout-small size warehouses.

Designing and analyzing a mixture experiment to optimize the mixing proportions of polyvinyl chloride composites

ABSTRACT Polyvinyl chloride (PVC) products are typically complex composites, whose quality characteristics vary widely depending on the types and proportions of their components, as well as other processing factors. It is often required to optimize PVC production for specific applications at the highest cost efficiency. This study describes the design and analysis of a statistical experiment to investigate the effects of different parameters over the mechanical properties of PVC intended for use in electrical wire insulation. Four commonly used mixture components, namely, virgin PVC, recycled PVC, calcium carbonate, and a plasticizer, and two process variables, type of plasticizer and filler particle size, were examined. Statistical tools were utilized to analyze and optimize the mixture while simultaneously finding the proper process parameters. The mix was optimized to achieve required strength and ductility, as per ASTM D6096 while minimizing cost. The paper demonstrates how statistical models can help tailor complex polymeric composites in the presence of variations created by process variables.

A Masters Programme in telecommunications management – demand-based curriculum design

This paper presents a curriculum design approach for a Masters Programme in Telecommunications Management based on demand data obtained from surveying the needs of potential students of the proposed programme. Through online surveys disseminated at telecom companies in Jordan, it was possible to measure the demand for such a programme and to determine the required programme contents and specifications. The curriculum design is based on definition of programme outcomes and on using a house of quality approach (HOQ) to determine the list of courses required in the programme. Surveyed competencies are mapped to a long list of proposed courses in a HOQ in order to determine the importance of each of these courses. A final list of core and elective courses is then developed considering the contribution to programme outcomes and the academic standards.