International Journal of Industrial Engineering and Productional Research
Volume:33 Issue: 4, Dec 2022

This study intends to evaluate the mediating role of employees performance in the relationship between delegation of authority, organizational functionality, and the decision making process among the employees of police department at Dubai. The study has collected data in the various police stations at Dubai from 380 employees through questionnaires based survey using random sampling technique. The study noted that employees performance has mediating role between the delegation of authority, organizational functionality, and the decision making process among the police employees at Dubai. The results of this research contributed substantially to the current body of knowledge in the domain of delegation of authority in Arab context. The novelty of this study stem from the reality that the issues and problems of power delegation in Dubai police department was assessed in terms of decision-making process.

Several industrial products such as moulds, dies, engine block, automotive parts, etc., require machining of a large number of holes. Similarly, applications like boiler plates, food-business processing separator's, printed circuit boards, drum and trammel screens, etc., consist of a matrix of a large number of holes. Many machining operations, such as drilling, enlargement, tapping, or reaming, are needed to achieve the final sizes of individual holes, resulting in a variety of possible sequences to complete the hole-making operations. The major issue involved in hole-making operations is the tool travel time. It is often vital to determine the optimal sequence of operations so that the overall processing cost of hole-making operations can be minimized. In this work, thus an attempt is made to minimize the total tool travel of hole-making operations by using a relatively new optimization algorithm known as modified shuffled frog leaping for the determination of the optimal sequence of operations. Modification is made in the present shuffled frog-leaping algorithm by using three parameters with their positive values in order to widen the search capability of the existing algorithm. This paper considers three case studies of a rectangular matrix of holes to explain the proposed procedure. The outcomes of optimization with a modified shuffled frog-leaping algorithm are compared to those obtained with the genetic algorithm and the ant colony algorithm. Additionally, the higher dimensional problem of 20 x 20 rectangular matrix of holes is considered in this work.

Supply chain management is one of the requirements for achieving economic growth in any supply chain. If managers' decisions are optimally allocated, it will be possible for companies and industries with a competitive and profitable advantage to grow and develop. The main desire of any company for survival is to minimize costs and maximize profitability. Due to the increasing complexity and dynamics of the situation, decision-making in this area requires more advanced analytical methods. Accordingly, the Real options theory has emerged, which introduces a new way of thinking about investing, especially in conditions of uncertainty. In this paper, a multi-period model is considered that examines the demand uncertainty in each period and also uses the Real options theory to seek the optimal strategy for investors in conditions of uncertainty and the effect of investors’ discretion on it. Using a decision tree to estimate the probable demand in each period and using Monte Carlo simulations to identify the lowest cost scenario in each period, the model has been solved in this research. In the case of the uncertainty parameter, sensitivity analysis is performed, and under different values ​​of this parameter, the obtained result is evaluated and validated. And the extension of outsourcing will increase the company’s profitability and meet higher demand and lower costs.

Healthy food can be perceived by looking at the label and packaging of the healthy food. Nutrition Claims and Nutrition Information printed as a labels and packaging of the healthy food. Nutrition Claims such as "Cholesterol Free" normally presented at the front of the healthy foods' package while nutrition information presented in a table with detailed information and printed at the back of the healthy foods' package. Previous researchers indicated that nutrition claims tends to be well received by consumers (Grunert, Wills & Fernandez-Celemin, 2010) compared to nutrition information. It seems that nutrition information seldom be useful to the customers. This is because nutrition information difficult to understand. However, nutrition information shows more detailed information regarding the product. Both nutrition claim and nutrition information printed as a label of the healthy foods' packaging. Besides that, colour of the packaging also plays an important role of the consumer perceptions towards healthy product. Label and packaging plays an important role for consumers’ perception. Nutrition information and nutrition claim that are appeared at the label and the colour of the packaging can model the consumers' perception on healthy food. This study will investigate the importance of nutrition information, nutrition claim and colour of the label and packaging towards consumers' perception on healthy foods. Data and survey will be conducted at Melaka. This study will use quantitative method and will conclude the independent variables that has significant influence towards consumers perception.

To develop a system for specific purpose, it needs to estimate its parameters (parameterization). It can be used in different fields like engineering, industry etc. In this work, authors used adaptive algorithm to model a system that is applicable in industry for control. This adaptive model is non-linear where its estimation is based on kernel based Least-mean square (LMS) algorithm. The kernel used as Polynomial and Gaussian. As the system is nonlinear polynomial kernel-based algorithm fails to prove its efficacy, though it is of low complexity approach. Gaussian kernel-based application for nonlinear system control performance better as compared to polynomial kernel. Further its complexity is reduced and used for faster performance. The result shows its performance in form of MSE, MAE, RMSE for identification and control that is very useful in industrial application.

This is a systematic literature review that discusses the contribution of fuzzy analytic (FA) and multi-criteria decision-making (MCDM) methods in classroom assessment. Due to lack of knowledge and not being exposed to the importance and benefits of using computational intelligence approaches such as FA and MCDM, not many educators apply such methods. The issue of how it operates is also the cause of educators still adopting conventional assessment methods. Classroom assessment involves the orientation of data in the form of divergent, multiple, fuzzy, and in terms of relation, so a more efficient approach of assessment is through modern mathematical methods and soft computing techniques as suggested by experts. This practical gap needs to be refined by providing a clear picture to educators about FA and MCDM as alternative assessment methods. Therefore, based on the PRISMA model, this systematic literature review is implemented to expose educators to the contribution of FA and MCDM in classroom assessment and conceptualize how to operate the method more easily and simply. Starting with article searches in several databases such as Google Scholar, ScienceDirect, and Elsevier using only specified keywords, 21 articles were selected for discussion after going through the steps of Identification, Screening, Eligibility and Included. Based on the findings, some aspects of assessment are very significant to be implemented using FA and MCDM, appropriate, more practical and show a meaningful contribution to classroom assessment. The conceptual model of the operation of FA and MCDM based on a summary of the workflow of selected studies can also help educators get insights and ideas to implement this alternative assessment method. This paper can prove that the computational intelligence approach greatly contributes to classroom assessment and if there are initiatives and facilitation implemented, surely educators can take advantage to strengthen the management and assessment of the classroom.

In this paper, a closed-loop supply chain is modeled based on hyperchaotic dynamics. Then, synchronization of the two hyperchaotic closed loop supply chains is performed with a proportional integral (PI) sliding mode controller design method. Using Lyapunov stability theory, it has been proved that the PI sliding mode controller can converge the synchronization error to zero in a limited time. The most important issue in the design of control strategies is the behavior of the control signal. In other words, it affects the cost of design and implementation. Numerical simulation results show that the control signal has low amplitude and fluctuations. so, the PI sliding mode control method can be implemented in the real world. Based on the numerical simulation results, the use of two controllers is proposed to reduce design costs.

The introduction of blockchain technology into the food supply chain represents a digital revolution that has led to widespread advances in tracking food security. This article presents a comprehensive review of the literature on the use of blockchain in the food supply chain. This article is a review of the synthesis evidence Best group. We have focused on the supply chains of meat, fruits and vegetables. The Literature review has been conducted from seven different databases. For more insight, we categorized meat, fruit, and vegetable articles into four groups: descriptive, prescriptive, conceptual, and predictive. Due to the small number of case studies in research, the theoretical and conceptual frameworks proposed in most food supply chain articles, including the supply chain of meat, fruits and vegetables, have been less tested in reality. These surveys and small-scale case studies do not clearly and completely identify the impact of blockchain on the meat, fruit and vegetable supply chain and the challenges that blockchain implementation may pose to these supply chains. Findings indicate that little valid and quality research has been done in this field and more research is needed on the use of blockchain in the supply chain of fresh products.

This paper aims to introduce a joint optimization approach for maintenance, quality, and buffer stock policies in single machine production systems based on a P control chart. The main idea is to find the optimal values of the preventive maintenance period, the buffer stock size, the sample size, the sampling interval, and the control limits simultaneously, such that the expected total cost per time unit is minimized. In the considered system, we have a fixed rate of production and stochastic machine breakdowns which directly affect the quality of the product. Periodic preventive maintenance (PM) is performed to reduce out-of-control states. In addition, corrective maintenance is required after finding each out-of-control state. A buffer is used to reduce production disturbances caused by machine stops. To ensure that demand is met during a preventive and corrective maintenance operation. All features of three sub-optimization problems including maintenance, quality control, and buffer stock policies are formulated and the proposed integrated approach is defined and modeled mathematically. In addition, an iterative numerical optimization procedure is developed to provide the optimal values for the decision variables. The proposed procedure provides the optimal values of the preventive maintenance period, the buffer stock size, the sample size, the sampling interval, and the control chart limits simultaneously, in a way that the total cost per time unit is minimized. Moreover, some sensitivity analyses are carried out to identify the key effective parameters.

Floating markets are not only a unique type of market but also sustainable tourist attractions. The literature focuses on both of floating market Covid-19 preventive measures and tourist’ satisfaction dimensions. The study is using quantitative research by concentrated on the tourist’s satisfaction of an anonymous Floating Market in Nakhon Pathom province. The research concentrated on the floating market Covid-19 preventive measures and the tourists’ satisfaction. The visitors certainly got great enjoyment from the floating market and this resulted in overall good experience for them better than most of them expected. The most important of Covid-19 preventive measures factors for the tourists were the provide clear entry, exit routes and screening point, merchants and customers always wear masks and provide hand washing points. The tourism component clearly overshadowed the destination shopping experience. The close proximity of the market to Bangkok contributes to the success of this market and the perceived satisfaction of the tourists

‎Recently, generalized distributions have received much attention due to their high applicability and flexibility. This paper introduces a new five-parameter distribution called Kumaraswamy-G generalized Gompertz distribution, which is widely used in the field of survival and lifetime data. In introducing a new distribution, it is important to study the statistical properties and the estimation of its parameters. Therefore, this paper studies the statistical properties of this new distribution. In addition, the parameters of this distribution are estimated by three methods. Finally, using a real dataset, the performance of the introduced distribution is investigated.

One of the problems faced by insurance companies, especially for the business class that has a long tail, is the length of the claim settlement period until the claim is paid off because there are procedures that must be carried out, such as analyzing and justifying the claims submitted. The claims that are still in the process are divided into two, namely claims that reported but have not been settled (RBNS) and claims that incurred but have not been reported (IBNR). One method that is often used in estimating claim reserves is the Chain Ladder Method. However, this method is only able to estimate the IBNR claim reserve. In 2012, Martinez-Miranda, Nielsen, and Verrall developed a method that can generate predictions of claim reserves for IBNR and RBNS separately, namely the Double Chain Ladder method. This study aims to calculate the estimated reserves for claim using Double Chain Ladder (DCL) method. From the calculation results, it is found that the Double Chain Ladder (DCL) method can estimate the IBNR and RBNS claim reserves clearly and separately with a total estimated RBNS claim reserve is 101.492,792 (in million rupiahs) and the estimated IBNR claim reserve is 29.172,880 (in million rupiahs).

Condition-based maintenance (CBM) is a well-known maintenance cost minimization strategy in which maintenance activities are performed based on the actual state of the system being maintained. The act of combining maintenance activities for different components is called opportunistic maintenance or maintenance clustering, which is known to be cost-effective, especially for multi-component systems with economic dependency. Every operating system is subject to gradual degradation which ultimately leads to system failure. Since each level of degradation can be represented by a state, every system can be modeled as a multi-state structure. The state of a system can be estimated through condition monitoring, albeit with uncertainty. The majority of studies in the field of maintenance planning are focused on preventive perfect maintenance operations such as replacement. But in practice, most of the maintenance operations are imperfect because of time, technology, and resource limitations. In this paper, we present a CBM clustering model that factors in uncertainty in alerting and lifetime distribution and considers the possibility of using the imperfect maintenance approach. This model is developed for a system with three levels of warning (Signal, Alert, Alarm), which combines inspections and condition monitoring to avoid unnecessary inspections and thereby achieve better cost-efficiency. Our analysis and results provide a general view of when and how to cluster maintenance activities to minimize maintenance costs and maximize system availability. Numerical investigations performed with MATLAB show that clustering CBM activities can result in as much as 80% cost saving compared to No clustering.

To develop a system for specific purpose, it needs to estimate its parameters (parameterization). It can be used in different fields like engineering, industry etc. In this work, authors used adaptive algorithm to model a system that is applicable in industry for control. This adaptive model is non-linear where its estimation is based on kernel based Least-mean square (LMS) algorithm. The kernel used as Polynomial and Gaussian. As the system is nonlinear polynomial kernel-based algorithm fails to prove its efficacy, though it is of low complexity approach. Gaussian kernel-based application for nonlinear system control performance better as compared to polynomial kernel. Further its complexity is reduced and used for faster performance. The result shows its performance in form of MSE, MAE, RMSE for identification and control that is very useful in industrial application.