Journal of Applied Research on Industrial Engineering
Volume:9 Issue: 2, Spring 2022

Exponential Weighted Moving Average (EWMA) control charts have been widely used in Statistical Process Control (SPC) to detect small and persistent process shifts. In theory, EWMA control limits monotonically increase over time to account for the continual growth of the EWMA statistic’s variance. However, these control limits are often assumed constant and are set to their respective asymptotic limits to simplify the process of applying and analyzing EWMA control charts. One-sided EWMA charts are often implemented when it is only desirable to detect shifts in a specific direction. When using one-sided EWMA charts, reflecting boundaries (resets) can be used to prevent the statistic from drifting too far from the chart’s control limit, which can delay shift detection. There have been several research efforts into designing and studying the performance of one-sided EWMA charts with reflecting boundaries. However, these efforts have maintained the constant control limit assumption. When implementing a reflecting boundary, the EWMA statistic’s variance is constantly being reset to zero, which may significantly affect the constant control limit assumption’s validity. The focus of this paper is to understand behavior of the one-sided EWMA control charts with constant and time-varying limit assumption through simulation studies.

Today, most supply chains are moving towards green business with a greater focus on environmental protection as a competitive advantage. Among them, the design of a three-stage green supply chain with optimal allocation, a multiple supply chain that includes supplier (first stage), manufacturer (second stage) and distributor (third stage), based on maximum efficiency and considering the internal processes and products between these three levels, can be of special importance; because, it will increase the economic and environmental performance of the supply chain. One of the methods used to evaluate efficiency in Green Supply Chain Management (GSCM) is Data Envelopment Analysis (DEA). Therefore, performance evaluation is vital for companies to improve the effectiveness and efficiency of the supply chain. In this study, using the three-stage approach of DEA, the data collected in 2020 from 9 Selected home appliance companies have been analyzed. The results show that company 1 has the best efficiency and the greenest supply chain and company 7 has the worst value of efficiency, which makes it necessary to pay more attention to low performance companies. In order to show the capability of the proposed model, the developed model was compared with its equivalent base model, and companies 1 and 2 were identified as inefficient in the proposed model, but identified as efficient in the base model. Given that the efficiency score in the proposed model is always lower than the base model, so the accuracy of the developed model can be concluded.

Bangladesh is blessed with various agro-based natural resources like Date sap, extracted from date trees. As this date sap is found in rural areas in large quantities annually but a very small fraction is converted into some value-added delicious foods at a domestic level while a large portion is left underutilized due to negligence, improper collection, and preservation system from the industry level. The processed delicious foods have conspicuous demand in the national market due to their nutritious value and the growth of the national economy. Despite its economic importance, very little researches have been conducted in this field for its industrial processing. So, this research implies to improve this straggled sector providing much attention for collecting raw sap from source and processing into value-added products from industrial level cost-effectively. The key objectives of this paper are to determine optimal facility location for processing date sap and set vehicle routes that can pick up date sap from source to processing plant simultaneously curtailing operational transportation costs. Initially, a Mixed Integer Linear Programming (MILP) model is introduced to determine optimal facility location. Besides, the Large Neighborhood Search (LNS) algorithm has been used to find the optimal set of vehicle routes. This paper outlines a summary of final results that Jessore (A south-western city in Bangladesh) is an optimal plant location and 10 vehicles are necessary for covering 15 areas which ultimately optimize the total supply time, respecting constraints concerning routing, timing, capacity, and supply as well transportation costs.

The personality in the present world plays a critical role in social interactions, the use of modern technologies, and individuals' success. Therefore, in the last two decades, the study of Automatic Personality Perception (APP) and Automatic Personality Recognition (APR) has become more prevalent than speech processing. These studies have shown that personality traits affect acoustic features. However, the intrinsic imbalanced distribution of personality classes across the dataset is an issue mentioned in most previous studies and the classification results suffer from it. In this paper, an innovative supervised k-fold Cross-Validation (CV) method was proposed to cope with the problem of affecting the imbalanced distribution of data across different classes. The classification outcomes showed better performance in comparison with three traditional data balancing methods. Moreover, the obtained results of the proposed evaluation method indicated that the proposed method acts as a k-fold CV method if the data distribution is balanced; otherwise, it will improve the classification results.

The pathology of a competency-based human resource management system results in the managers developing appropriate schedules for employee growth and excellence to gain a competitive advantage. The present study is meant to be an applied study of a descriptive exploratory nature. Information and data gathering involves library and field research making use of interviews and questionnaires. The statistical population of this study is comprised of experts including 10 human resource managers and chief officers, selected using a targeted method. The components were determined and analyzed using the experts' opinions and the Delphi method; furthermore, by implementing the importance-performance analysis, low-performance but high-importance components were categorized in 6 groups of "Human Resource Supply System", "Human Resource Training and Development System", "Human Resource Retention System", "Human Resource Labor Relations System", "Human Resource Performance Management System", "Human Resource Reward System". Moreover, to rectify the problems, the Fuzzy DEMATEL method was implemented with the results showing the "Human Resource Supply System" problem to be the most effective, eventually leading to the problem of "Human Resource Performance Management System", is the most affected. Managers can reach a desirable human resource management system by identifying individuals of professional competence to compete in a dynamic economy.

One of the main topics with increasing interest in freight transport and logistics is developing efficient and sustainable supply chain strategies that best cover customer demands and expectations as well as identify considerable cost savings and emission reductions. This study focuses on the evaluation of the potential of a logistics centre for consolidating and delivering goods at urban level, based on economic, social and environmental aspects, by performing both GIS simulation and SWOT analysis, while considering key criteria of transport management, infrastructure and fleet attributes as well as logistics and market features in the Attica region of Greece. The case refers to the largest Logistics Centre of Greece, located at Thriasio, offering door-to door services to the main industrial areas of the region. The approach followed, consists of two core elements: a) a specific model of a last-mile delivery network in GIS environment, towards simulating and solving the Vehicle Routing Problem (VRP) as well as b) a strategic assessment of the foreseen logistics activities through the SWOT business tool. For a transport operator with 5 vehicles, an operational distance-related cost of €1.8-1.9 per pallet was estimated. Results also show the lower environmental impact of larger vehicles due to transport pooling.

The present study aims at presenting a model of cross-buying behavior of electronic service customers in Shahr Bank. This research is applied in terms of objective and survey-exploratory in terms of approach. The statistical population of this study consisted of a group of experts including senior managers of Shahr Bank, professors and marketing consultants familiar with the banking industry which in-depth interviews were conducted with them. The selection of experts and doing interviews with them continued until the theoretical saturation was reached and then stopped. Purposive sampling method was used in this study. Nine interviews were conducted in total. This research has been done in the period of October 2020 to May 2021. Due to using the data foundation theory in this research, the main data collection tool was unstructured in-depth interviews with experts. Finally, after three open, axial and selective kinds of coding, the conceptual model of the research was designed based on a paradigm model. In this research and according to the identified goals and categories, the category of motivating to use various electronic services of Shahr Bank was considered as the main and axial category. This means that the core of the conceptual model is the users' motivation and inner desire to use various electronic services of this bank.

The Single-Minute Exchange of Dies (SMED) methodology proved to be an effective approach for reducing setup times on a bottleneck 66” Koppers rotary die-cutter machine center in a corrugated box plant. Root cause analysis techniques, such as a check sheet and control charts, aided the analysis. The supervisor and work crew, consisting of both the operator and setup person, played an integral role in reducing setup times by consenting to being videotaped during a typical setup and then breaking down the video to distinguish internal versus external steps. By converting many internal steps to external steps, average setup times were reduced from 55 minutes to 32 minutes, a 42% improvement.

A Cellular Manufacturing System (CMS) is a suitable system for the economic manufacture of part families. Scheduling the manufacturing cells plays an effective role in successful implementation of the manufacturing system. Due to the fact that in the CMS, bottleneck machine and human resources are two important factors, which so far have not been studied simultaneously in a mathematical model, there should be a model to consider them. Therefore, this research develops a bi-objective model for CMS in a three-dimensional space of machine-part and human resources. The main objective is to minimize the maximum completion time of all tasks in the system and reduce the number of intercellular translocation based on bottleneck machines’ motion and human resources. Due to the NP-hardness of the studied problem, applying the conventional solution methods is very time-consuming, and is impossible in large dimensions. Therefore, the use of metaheuristic methods will be useful. The accuracy of the proposed model is investigated using LINGO by solving a small example. Then, to solve the problem in larger dimensions, a hybrid Multi-Objective Tabu Search-Genetic Algorithm (MO-TS-GA) is designed and numerical results are reported for several examples.

This paper, presents a mathematical model of a four-level supply chain under hyperchaos circumstances. The analysis of this model shows that the hyper-chaotic supply chain has an unstable equilibrium point. Using Lyapunov's theory of stability, the problem of designing a hyperchaotic supply chain control is investigated. The design of the nonlinear controller is performed first to synchronize two identical hyper-chaotic systems with different initial conditions and then to eliminate the chaotic behavior in the supply chain and move to one of unstable equilibrium points, as well as different desired values ​​at different times. A different supply chain is predicted to demonstrate the performance of the controller. In the next part of numerical simulation, with the control of the distributor as the center of gravity of the model, the stability of the entire chaotic supply chain can be achieved.  The most important point in designing a control strategy is the ability to implement it in the real world. Numerical simulation results in all stages show that the applied nonlinear control policy can provide supply chain stability in a short period of time, also, the behavior of control signals has low amplitude and oscillations. In other words, it represents a low cost to control the hyperchaotic supply chain network.