Journal of Applied Research on Industrial Engineering
Volume:10 Issue: 3, Summer 2023

The floor tiles industry in accordance with state regulations is one of the manufacturing industries that can participate in Indonesia into a developed industrial country, supported by the availability of various technologies and product innovations so that domestic floor tiles can be accepted. In the face of increasing competition, domestic floor tiles industry trying to improve the quality of the products by implementing a strict standardization system for production processes and products produced by implementing Total Quality Management (TQM). Based on the components that influence of TQM, variables of leadership, technical competence and organizational culture are closely related to certain factors. A leadership pattern that focuses on goals or targets determined and taken based on scientific thinking by taking into account the various parties involved will improve the quality. Education and training as well as employee involvement by providing controlled independence as well as improving the technical quality.

This study considered the consequence of the length and weight composition percentage of Deleb palm fruit fiber on the physio-mechanical characteristics of an epoxy-based composite through the Taguchi grey relational optimization technique. Considering fiber reinforcement of 30 wt% to 40 wt% and fiber Reinforcement Length (RL) of 1-5 mm, the physical and mechanical properties were determined based on standards. The findings demonstrated that the Deleb palm fruit fiber's characteristics tend to differ from those of other types of fiber reinforcement in that they significantly impact the physio-mechanical characteristics of the resulting epoxy-based reinforced Deleb palm fruit fiber composite. The  Analysis of Variance (ANOVA) result showed that, at a confidence interval of 5%, the effects of the fiber characteristics on the physio-mechanical properties of the composites were particularly notable for tensile strength and a decrease in water absorption.

Due to the importance of the health field, the problem of determining the shift scheduling of care providers has been addressed in many studies, and various methods have been proposed to solve it. Considering different skills and contracts for care providers is one of the essential issues in this field. Given the uncertainty in patients' demands, it is a crucial issue as to how to assign care providers to different shifts. One area facing this uncertainty is the provision of services to cancer patients. This study develops a stochastic programming model to account for patient demand uncertainty by considering different skills and contracts for care providers. In the first step, care providers are assigned to work shifts, then, in the second step, the required overtime hours are determined. The sample average approximation method is presented to determine an optimal schedule by minimizing care providers' regular and overtime costs with different contracts and skills. Then, the appropriate sample size is 100, determined based on the Monte Carlo and Latin Hypercube methods. In the following, the lower and upper bounds of the optimal solution are calculated. As the numerical results of the study show, the convergence of the lower and upper bounds of the optimal solution is obtained from the Latin Hypercube method. The best solution is equal to 189247.3 dollars and is achieved with a difference of 0.143% between the upper bound and lower bounds of the optimal solution. The Monte Carlo simulation method is used to validate the care provider program in the next stage. As shown, in the worst case, the value of the objective function is equal to 197480 dollars.

This paper presents an optimization model for hotel pricing in the competitive environment following the Covid-19 epidemic, in which the government intervenes by offering appropriate tariffs and hotels use incentive policies such as discounts to attract customers. we consider the government as the leader and the hotels as the followers of the Stalkberg model, then apply the Nash equilibrium to determine the optimal price and demand of hotels in competitive conditions, taking into account the discount. By considering a government utility function, the optimal level of government tariffs is determined. The results indicate that government intervention in the tourism industry includes measures that benefit tourism. Because the government can increase the hotel revenue and expand tourism in favor of hoteliers by reducing its profits. Extensive analysis has been performed on five-star, four-star, and three-star hotels in a tourist area in Iran, and some of the most important managerial insights have been explained.

To evaluate the performance and estimate the efficiency of Decision-Making Units (DMUs) in Data Envelopment Analysis (DEA), the available data are used. These data are usually divided into two categories of inputs and outputs based on their natures. If the price data is also available for inputs, it is necessary to calculate another type of the efficiency called Cost Efficiency (CE). Since the efficiency of units in such a framework is depended on the both quantities of inputs and outputs and also the prices of inputs, it is important to find the sources of cost inefficiency related to each of the factors and plans to address them. In this paper, we intend to present a new decomposition of CE and observed cost versus optimal cost, which are raised from each of the factors involved in the cost inefficiency, in a non-competitive pricing environment which the input price vector for different DMUs can be different. Moreover, for the first time, in parallel with using the PPS based on input and output quantities and introducing some cost inefficiency factors related to this set, we will introduce new sets called price and cost production sets that the first is based on the prices of inputs and output factors, and the second is based on the optimal vectors of inputs and prices obtained from two previous PPS, and then we will introduce other factors of cost inefficiency in the sets. Accordingly, new decomposition for cost inefficiencies will be presented. Also, in the previous analyzes, congestion inefficiency has not been considered as one of the important factors in cost inefficiency. In this study, we also intend to consider the impact of this factor on CE.

Today, logistics costs often make up a major part of large organizations’ expenses. These costs can be reduced with optimal design and its implementation in the supply chain. As a result, in present study, a two-objective mathematical location-routing model is presented, where an objective is to minimize the costs and the next is to maximize the reliability in order to deliver the goods timely to customer according to the probable time and time window. The proposed problem has two levels of distribution. The first level, which is called transportation level, points to the distribution of products from a factory to an open distribution center, and the latter is known as routing level, which is related to a part of the problem in which we deliver products from the warehouse to customers. The proposed mathematical model is solved by Epsilon-constraint and NSGA-II approaches in small and medium, and large scales problem, respectively. The present study has provided the following contributions: concurrent locating and routing in the supply chain in accordance with the customer’s time window, probable travel time in the supply chain and customer’s reliability in the supply chain. The assessment metric results indicate the proper performance of our proposed model.

The natural disasters of the last few decades clearly reveal that natural disasters impose high financial and human costs on governments and communities. Concerns in this regard are growing day by day. Making the right decisions and taking appropriate and timely measures in each phase of the crisis management cycle will reduce potential damage at the time of the disaster and reduce the vulnerability of society. Therefore, in this research, a mathematical model of crisis logistics planning considering the problem of primary and secondary crisis in disaster relief is introduced, which is the innovation of this research. In the primary crisis, the goal is to provide services and relief goods to crisis areas, and in the second stage, the secondary crisis that occurs after the primary crisis seeks to provide relief to crisis centers and transfer the injured to relief centers.  Therefore, this research proposes a mathematical fuzzy ideal programming model in two primary and secondary crises. In the primary crisis, the goal is to provide services and relief goods to crisis-stricken areas. The secondary crisis, which occurs after the primary crisis, aims to support crisis-stricken centers and move injured people to relief bases in the second step. According to the proposed model, Bertsimas-Sim’s fuzzy programming that formulation proposed by Bertsimas and Sim [1] and robust approach we initially used. The Epsilon constraint method was used to solve the low-dimensional model. Multi-objective meta-heuristic algorithms have been designed to handle the computational complexity of large-scale real-time problems. Multiple comparisons and analyses have been proposed to assess the performance of the model and problem-solving capabilities. The results indicate that the proposed approach can be applied and implemented to develop a real-world humanitarian logistics network.

In this article, a mathematical model of the inverse problem is considered. Based on this model a formulation of inverse problem for heat equation is proposed. Shifted Chebyshev Tau (SCT) method is suggested to solve the inverse problem. The aim of this determined effort is to identify unknown function and unknown control parameter of the mathematical model. In order to achieve highly accurate solution to this problem, the operational matrix of shifted Chebyshev polynomials is investigated in conjunction with tau scheme. To demonstrate the validity and applicability of the developed scheme, numerical example is presented.

The primary purpose of this research was to understand the importance of supply chain strategies in the field of supply chain risk management, emphasizing the effectiveness and efficiency of agile and lean strategies to create resilience and robustness in the supply chain. Data was collected from 392 supply chain experts working in Iran's automotive industry to test hypotheses through structural equation modeling. The findings of this study show that Market Orientation (MO) (as an external force) has more signicant impact on the development of Agile Strategy (AS) than Lean Strategy (LS). In contrast, the Quality Management (QM) system (as an internal force) is highly correlated with the development of lean supply chain strategies. Moreover, agile and lean strategies also have a signicant impact on a resilient and Robust Supply Chain (RB). The proposed model helps organizations understand and create an ideal supply chain by implementing the right combination of both agile and lean supply chain strategies, which in turn helps to create a resilient and RB. Therefore, the findings of this study help policymakers to improve supply chain strategies by incorporating new management practices. This is original research that has various valuable insights for academic researchers and also supply chain strategy professionals as it reveals empirical evidence of the past vital concepts.

This single case study examined how key internal audit planning and implementation determinants impacted a South African automotive company's ISO 9001 Quality Management System (QMS) objectives. The study used a mixed method approach; qualitative data nesting in quantitative data. The purposive sampling technique was used to collect primary data from managers, internal quality auditors, and auditees. Professional judgment was used to collect secondary data from the 2017 to 2020 audit reports. Descriptive data analysis was conducted on the data collected. The internal audits were conducted beyond departmental boundaries and organizational structures. The audit determinants were; compliance with the ISO 9001 standards, and maintenance of ISO 9001 QMS certification. The process and system internal quality audits were conducted to correct nonconformities before and after external audits. Audit reports from certification bodies also determined the scope of the subsequent internal audit programs for processes and systems. In addition, the internal auditors relied on their judgments and on the technical experts' advice to sample processes, areas, and material to be audited. management audit review reports also contributed to determining the scope of audit programs. Despite different stakeholders' contributions, the company's internal quality audit programs did not embrace customer focus and continuous improvement. The audit program was a reaction to internal and external stakeholders' complaints. However, the study is fundamental to improving the company's ISO 9001 QMS performance. It discusses issues that drive the planning and implementation of audit programs. The findings are likely to stimulate similar research in other sectors and on a bigger scale. There are also opportunities to evaluate the determinants related to monitoring, reviewing, and improving audit programs.