Search results for: inventory constraints

Authors: Gamze Sekeroglu, Mikail Altan

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Working capital is identified as firm’s all current assets. Inventories which are one of the working capital elements are very important among current assets for firms. Because, profitability is an indicator for firms’ financial success is provided with minimum cost and optimum inventory quantity. So in this study, it is investigated as comparatively that the effect of inventory management on the profitability of Turkish firms which operated in weaving industry, eatables industry, wholesale and retail industry in between 2003 – 2012 years. Research data consist of profitability ratios and inventory turnovers ratio calculated by using balance sheets and income statements of firms which operated in Borsa Istanbul (BIST). In this research, the relationship between inventories and profitability is investigated by using SPSS-20 software with regression and correlation analysis. The results achieved from three industry departments which exist in study interpreted as comparatively. Accordingly, it is determined that there is a positive relationship between inventory management and profitability in eatables industry. However, it was founded that there is no relationship between inventory management and profitability in weaving industry and wholesale and retail industry.

Keywords: profitability, regression analysis, inventory management, working capital

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Authors: Esha Saha, Pradip Kumar Ray

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A hospital inventory comprises of a large number and great variety of items for the proper treatment and care of patients, such as pharmaceuticals, medical equipment, surgical items, etc. Improper management of these items, i.e. stockouts, may lead to delay in treatment or other fatal consequences, even death of the patient. So, generally the hospitals tend to overstock items to avoid the risk of stockout which leads to unnecessary investment of money, difficulty in storing, more expiration and wastage, etc. Thus, in such challenging environment, it is necessary for hospitals to follow an inventory policy considering the stochasticity of demand in a hospital. Statistical analysis captures the correlation of patient condition based on bed occupancy with the patient demand which changes stochastically. Due to the dependency on bed occupancy, the markov model is developed that helps to map the changes in demand of hospital inventory based on the changes in the patient condition represented by the movements of bed occupancy states (acute care state, rehabilitative state and long-care state) during the length-of-stay of patient in a hospital. An inventory policy is developed for a hospital based on the fulfillment of patient demand with the objective of minimizing the frequency and quantity of placement of orders of inventoried items. The analytical structure of the model based on probability calculation is provided to show the optimal inventory-related decisions. A case-study is illustrated in this paper for the development of hospital inventory model based on patient demand for multiple inpatient pharmaceutical items. A sensitivity analysis is conducted to investigate the impact of inventory-related parameters on the developed optimal inventory policy. Therefore, the developed model and solution approach may help the hospital managers and pharmacists in managing the hospital inventory in case of stochastic demand of inpatient pharmaceutical items.

Keywords: bed occupancy, hospital inventory, markov model, patient condition, pharmaceutical items

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Authors: Ismayanti Magfirah, Sartohadi Junun, Samodra Guruh

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Landslides are one of the most frequent and devastating natural disasters in Indonesia. Many studies have been conducted regarding this phenomenon. However, there is a lack of attention in the landslide inventory mapping. The natural condition (dense forest area) and the limited human and economic resources are some of the major problems in building landslide inventory in Indonesia. Considering the importance of landslide inventory data in susceptibility, hazard, and risk analysis, it is essential to generate landslide inventory based on available resources. In order to achieve this, the first thing we have to do is identify the landslides' location. The presence of Sentinel-1A and Sentinel-2A data gives new insights into land monitoring investigation. The free access, high spatial resolution, and short revisit time, make the data become one of the most trending open sources data used in landslide mapping. Sentinel-1A and Sentinel-2A data have been used broadly for landslide detection and landuse/landcover mapping. This study aims to generate landslide map by integrating Sentinel-1A and Sentinel-2A data use change detection method. The result will be validated by field investigation to make preliminary landslide inventory in the study area.

Keywords: change detection method, landslide inventory mapping, Sentinel-1A, Sentinel-2A

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Authors: Madhu Babu Cherukuri, Tamoghna Ghosh

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Factory supply chain management spends billions of dollars every year to procure and manage equipment spare parts. Due to technology -and processes changes some of these spares become obsolete/dead inventory. Factories have huge dead inventory worth millions of dollars accumulating over time. This is due to lack of a scientific methodology to identify them and send the inventory back to the suppliers on a timely basis. The standard approach followed across industries to deal with this is: if a part is not used for a set pre-defined period of time it is declared dead. This leads to accumulation of dead parts over time and these parts cannot be sold back to the suppliers as it is too late as per contract agreement. Our main idea is the time period for identifying a part as dead cannot be a fixed pre-defined duration across all parts. Rather, it should depend on various properties of the part like historical consumption pattern, type of part, how many machines it is being used in, whether it- is a preventive maintenance part etc. We have designed a predictive algorithm which predicts part obsolescence well in advance with reasonable accuracy and which can help save millions.

Keywords: obsolete inventory, machine learning, big data, supply chain analytics, dead inventory

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Authors: Riccardo Patriarca, Giulio Di Gravio, Francesco Costantino, Massimo Tronci

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An accurate inventory management policy acquires a crucial role in the several high-availability sectors. In these sectors, due to the high-cost of spares and backorders, an (S-1, S) replenishment policy is necessary for high-availability items. The policy enables the shipment of a substitute efficient item anytime the inventory size decreases by one. This policy can be modelled following the Multi-Echelon Technique for Recoverable Item Control (METRIC). The METRIC is a system-based technique that allows defining the optimum stock level in a multi-echelon network, adopting measures in line with the decision-maker’s perspective. The METRIC defines an availability-cost function with inventory costs and required service levels, using as inputs data about the demand trend, the supplying and maintenance characteristics of the network and the budget/availability constraints. The traditional METRIC relies on the hypothesis that a Poisson distribution well represents the demand distribution in case of items with a low failure rate. However, in this research, we will explore the effects of using a Poisson distribution to model the demand of low failure rate items characterized by an irregular demand trend. This characteristic of a demand is not included in the traditional METRIC formulation leading to the need of revising its traditional formulation. Using the CV (Coefficient of Variation) and ADI (Average inter-Demand Interval) classification, we will define the inherent flaws of Poisson-based METRIC for irregular demand items, defining an innovative ad hoc distribution which can better fit the irregular demands. This distribution will allow defining proper stock levels to reduce stocking and backorder costs due to the high irregularities in the demand trend. A case study in the aviation domain will clarify the benefits of this innovative METRIC approach.

Keywords: METRIC, inventory management, irregular demand, spare parts

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Authors: Qamar Iqbal

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Companies strive to improve their forecasting methods to predict the fluctuations in customer demand. These fluctuation and variation in demand affect the manufacturing operations and can limit a company’s ability to fulfill customer demand on time. Companies keep the inventory buffer and maintain the stocking levels to reduce the impact of demand variation. A mid-size company deals with thousands of stock keeping units (skus). It is neither easy and nor efficient to control and manage each sku. Inventory classification provides a tool to the management to increase their ability to support customer demand. The paper presents a framework that shows how inventory classification can play a role to increase supply chain responsiveness. A case study will be presented to further elaborate the method both for build-to-order and build-to-forecast manufacturing environments. Results will be compared that will show which manufacturing setting has advantage over another under different circumstances. The outcome of this study is very useful to the management because this will give them an insight on how inventory classification can be used to increase their ability to respond to changing customer needs.

Keywords: inventory classification, supply chain responsiveness, forecast, manufacturing environment

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Authors: Muhammad Waseem Akram

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The current study attempts to analyze the impact of business constraints on the growth potential and performance of Small and Medium Enterprises (SMEs) in the electrical industry of Pakistan. Primary data have been utilized for the study collected from the electrical industry cluster in Sargodha, Pakistan. OLS regression is used to assess the impact of business constraints on the performance of SMEs by controlling the effect of Technology Level, Innovations, and Firm Size. To associate business constraints with the growth potential of SMEs, the study utilized Tetrachoric Correlation and Logistic Regression. Findings reveal that all the business constraints negatively affect the performance of SMEs in the electrical industry except Political Instability. Results of Tetrachoric Correlation show that all the business constraints are negatively correlated with the growth potential of SMEs. Logistic Regression results show that Energy Constraint, Inflation and Price Instability, and Bad Business Practices, all three business constraints cause to reduce the probability of income growth in sample SMEs.

Keywords: SMEs, business constraints, performance, growth potential

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Authors: Israel Becerril Rosales, Manuel González De La Rosa, Gerardo Villa Sánchez

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In this work, the effects that produce not having a good inventory management is analyzed, in addition of the way that how it affects the storage costs. The research began conducting the historical analysis about stored products, its storage capacity, and distribution. The results were not optimal, since in all its raw materials (RM) have overstocking, the warehouse capacity is only used by 61%, does not have a specific place for each of its RM, causing that the delivery times increases and makes difficult a cyclical inventory. These shortcomings allowed to view and select as design alternatives the inventory ABC, so that depending on the consumption of each RM would be redistributed by using economic amount requested. Also, the Delphi method to ensure the practical applicability of the proposed tool was used, taking in account comments and suggestions of the involved experts, as well as the compliance of NOM-059-SSA1-2015 good manufacturing practices of drug. With the actions implemented, the utilization rate drops of 61% to 32% capacity, it shows that the warehouse was not designed properly due to there is not an industrial engineering area.

Keywords: lead time, improve delivery, storage costs, inventory management

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Authors: Noha Nagy, Hoda Mokhtar, Mohamed El Sherkawi

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The popularity of workflow delegation models and the increasing number of workflow provenance-aware systems motivate the need for finding more strict delegation models. Such models combine different approaches for enhanced security and respecting workflow privacy. Although modern enterprises seek conformance to workflow constraints to ensure correctness of their work, these constraints pose a threat to security, because these constraints can be good seeds for attacking privacy even in secure models. This paper introduces a comprehensive Workflow Delegation Model (WFDM) that utilizes provenance and workflow constraints to prevent malicious delegate from attacking workflow privacy as well as extending the delegation functionalities. In addition, we argue the need for exploiting workflow constraints to improve workflow security models.

Keywords: workflow delegation models, secure workflow, workflow privacy, workflow provenance

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Authors: Min Dai, Hong Liu, Shuaijie Qian

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We study a portfolio selection problem of an investor who faces constraints on rebalancing frequency, which is common in pension fund investment. We formulate it as a multiple optimal stopping problem and utilize the dynamic programming principle. By numerically solving the corresponding Hamilton-Jacobi-Bellman (HJB) equation, we find a series of free boundaries characterizing optimal strategy, and the constraints significantly impact the optimal strategy. Even in the absence of transaction costs, there is a no-trading region, depending on the number of the remaining trading chances. We also find that the equivalent wealth loss caused by the constraints is large. In conclusion, our model clarifies the impact of the constraints on transaction frequency on the optimal strategy.

Keywords: portfolio selection, rebalancing frequency, optimal strategy, free boundary, optimal stopping

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Authors: Nisa Nur Duman, Sümeyya Kiliç

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In global competition conditions, survival of the plants by obtaining competitive advantage relies on the effective usage of existing sources. By this way, the plants can minimize their costs without losing their quality. They also take advantage took advantage on their competitors and enlarge customer portfolio by increasing profit margins. Changing structure of market and customer demands also change the structure of the competition between companies. Furthermore, competition is not only between the companies. By this manner, supply chain and supply chain management get importance by considering company performances. Companies that want to survive, search the ways of decreasing costs and the ways of meeting customer expectations. One of the important tools for reaching these goals is inventory managemet. The best inventory management system is meeting the demands by considering plant goals.

Keywords: Supply chain, inventory management, apparel sector, garment industry

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Authors: Elham Ahmadi, Roshaali Khaturia, Pardis Sahraei, Mohammad Niyayesh, Omid Fatahi Valilai

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Nowadays, Information Technology (IT) is changing the way traditional enterprise management concepts work. One of the most dominant IT achievements is the Blockchain Technology. This technology enables the distributed collaboration of stakeholders for their interactions while fulfilling the security and consensus rules among them. This paper has focused on the application of Blockchain technology to enhance one of traditional inventory management models. The Vendor Managed Inventory (VMI) has been considered one of the most efficient mechanisms for vendor inventory planning by the suppliers. While VMI has brought competitive advantages for many industries, however its centralized mechanism limits the collaboration of a pool of suppliers and vendors simultaneously. This paper has studied the recent research for VMI application in industries and also has investigated the applications of Blockchain technology for decentralized collaboration of stakeholders. Focusing on sustainability issue for total supply chain consisting suppliers and vendors, it has proposed a Blockchain based VMI conceptual model. The different capabilities of this model for enabling the collaboration of stakeholders while maintaining the competitive advantages and sustainability issues have been discussed.

Keywords: vendor managed inventory, VMI, blockchain technology, supply chain planning, sustainability

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Authors: Suhair Mereish

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This research is aimed at examining the climate for innovation in organisations with the aim of validating the psychometric properties of the Team Climate Inventory (TCI -14) for Jordan’s collectivist society. The innovativeness of teams may be improved or obstructed by the climate within the team. Further, personal factors are considered an important element that influences the climate for innovation. Accordingly, measuring the employees' personality traits using the Big Five Inventory (BFI-44) could provide insights that aid in understanding how to improve innovation. Thus, studying the climate for innovation and its associations with personality traits is valuable, considering the insights it could offer on employee performance, job satisfaction, and well-being. Essentially, the Team Climate Inventory instrument has never been tested in Jordan’s collectivist society. Accordingly, in order to address the existing gap in the literature as a whole and, more specifically, in Jordan, it is essential to investigate its factorial structure and reliability in this particular context. It is also important to explore whether the factorial structure of the Team Climate Inventory in Jordan’s collectivist society demonstrates a similar or different structure to what has been found in individualistic ones. Lastly, examining if there are associations between the Team Climate Inventory and personality traits of Jordanian employees is pivotal. The quantitative study was carried out among Jordanian employees employed in two of the top 20 companies in Jordan, a shipping and logistics company (N=473) and a telecommunications company (N=219). To generalise the findings, this was followed by collecting data from the general population of this country (N=399). The participants completed the Team Climate Inventory. Confirmatory factor analyses and reliability tests were conducted to confirm the factorial structure, validity, and reliability of the inventory. Findings presented that the four-factor structure of the Team Climate Inventory in Jordan revealed a similar structure to the ones in Western culture. The four-factor structure has been confirmed with good fit indices and reliability values. Moreover, for climate for innovation, regression analysis identified agreeableness (positive) and neuroticism (negative) from the Big Five Inventory as significant predictors. This study will contribute to knowledge in several ways. First, by examining the reliability and factorial structure in a Jordanian collectivist context rather than a Western individualistic one. Second, by comparing the Team Climate Inventory structure in Jordan with findings for the Team Climate Inventory from Western individualistic societies. Third, by studying its relationships with personality traits in that country. Furthermore, findings from this study will assist practitioners in the field of organisational psychology and development to improve the climate for innovation for employees working in organisations in Jordan. It is also expected that the results of this research will provide recommendations to professionals in the business psychology sector regarding the characteristics of employees who hold positive and negative perceptions of the workplace climate.

Keywords: big five inventory, climate for innovation, collectivism, individualism, Jordan, team climate inventory

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Authors: Rushiraj Heshi, Smriti Bhandari

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Master Data Management requires creation of Central repository, applying constraints on Repository and designing processes to manage data. Designing of Repository, constraints on repository and business processes is very tedious and time consuming task for large Enterprise. Hence Visual Repository, constraints and Process (Workflow) modeling is the most critical step in Master Data Management.In this paper, we realize a Visual Modeling tool for implementing Repositories, Constraints and Processes based on Eclipse Plugin using GMF/EMF which follows principles of Model Driven Engineering (MDE).

Keywords: EMF, GMF, GEF, repository, constraint, process

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Authors: Amir Andria Gad Shehata

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Minimizing the inventory cost, optimizing the inventory quantities, and increasing system operational availability are the main motivations to enhance forecasting demand of spare parts in a major power utility company in Medina. This paper reports in an effort made to optimize the orders quantities of spare parts by improving the method of forecasting the demand. The study focuses on equipment that has frequent spare parts purchase orders with uncertain demand. The pattern of the demand considers a lumpy pattern which makes conventional forecasting methods less effective. A comparison was made by benchmarking various methods of forecasting based on experts’ criteria to select the most suitable method for the case study. Three actual data sets were used to make the forecast in this case study. Two neural networks (NN) approaches were utilized and compared, namely long short-term memory (LSTM) and multilayer perceptron (MLP). The results as expected, showed that the NN models gave better results than traditional forecasting method (judgmental method). In addition, the LSTM model had a higher predictive accuracy than the MLP model.

Keywords: spare part, spare part inventory, inventory model, optimization, maintenanceneural network, LSTM, MLP, forecasting demand, inventory management

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Authors: Lin Fu-Gong

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Background: As WHO announced, people with intellectual disability (ID) were vulnerable to mental health problems. And there were few custom-made mental health scales for those people to monitor their mental health. Those people with mental problems often accompanied worse prognosis and usually became to be a heavier burden on the caregivers. Purpose: In this study, we intend to develop a psychopathy scale as a practical tool for monitoring the mental health for people with ID living in institute. Methods: In this study, we adopt the Psychopathology Inventory for Mentally Retarded Adults developed by professor Matson with certified reliability and validity in Western countries with Dr. Matson’s agreement in advance. We first translated the inventory into Chinese validated version considering the domestic culture background in the past year. And the validity and reliability evaluation of mental health status using this inventory among the people with intellectual living in the institute were done. Results: The inventory includes eight psychiatric disorder scales as schizophrenic, affective, psychosexual, adjustment, anxiety, somatoform, personality disorders and inappropriate mental adjustment. Around 83% of 40 invested people, who randomly selected from the institute, were found to have at least one disorder who were recommended with medical help by two evaluators. Among the residents examined, somatoform disorder and inappropriate mental adjustment were most popular with 60% and 78% people respectively. Conclusion: The result showed the prevalence psychiatric disorders were relatively high among people with ID in institute and the mental problems need to be further cared and followed for their mental health. The results showed that the psychopathology inventory was a useful tool for institute caregiver, manager and for long-term care policy to the government. In the coming stage, we plan to extend the use of the valid Chinese version inventory among more different type institutes for people with ID to establish their dynamic mental health status including medical need, relapse and rehabilitation to promote their mental health.

Keywords: intellectual disability, psychiatric disorder, psychopathology inventory, mental health, the institute

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Authors: Raja Kannusamy

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The research focuses on reducing food waste in the restaurant industry. A study has been conducted on the chain of retail restaurant outlets. It has been observed that the food wastages are due to the inefficient inventory management systems practiced in the restaurant outlets. The major food items which are wasted more in quantity are being selected across the retail chain outlets. A moving average forecasting method has been applied for the selected food items so that their future demand could be predicted accurately and food wastage could be avoided. It has been found that the moving average prediction method helps in predicting forecasts accurately. The demand values obtained from the moving average method have been compared to the actual demand values and are found to be similar with minimum variations. The inventory optimization technique helps in reducing food wastage in restaurant supply chain outlets.

Keywords: food wastage, restaurant supply chain, inventory optimisation, demand forecasting

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Authors: Tao Zhang

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Job stress appears nearly everywhere especially in the hospitality industry because employees in this industry usually have to work long time and try to meet conflicting demands of their customers, managers, and company. To reduce job stress, employees of casino hotels try to perform leisure activities or tourism. However, casino employees often meet many obstacles or constraints when they plan to travel. Until now, there is little understanding as to why casino hotel employees often face many travel constraints or leisure barriers. What is more, few studies explore the relationship between travel constraints and job stress of casino employees. Therefore, this study is to explore the construct of casino hotel employees' travel constraints and the relationship among job stress, travel constraints, and job satisfaction. Using convenient sampling method, this study planned to investigate 500 front line employees and managers of ten casino hotels in Macau. A total of 500 questionnaires were distributed, and 414 valid questionnaires were received. The return rate of valid questionnaires is 82.8%. Several statistical techniques such as factor analysis, t-test, one-way ANOVA, and regression analysis were applied to analyze the collected data. The findings of this study are as follows. Firstly, by using factor analysis, this study found the travel constraints of casino employees include intrapersonal constraints, interpersonal constraints, and structural constraints. Secondly, by using regression analysis, the study found travel constraints are positively related with job stress while negatively related with job satisfaction. This means reducing travel constraints may create a chance for casino employees to travel so that they could reduce job stress, therefore raise their job satisfaction. Thirdly, this research divided the research samples into three groups by the degree of job stress. The three groups are low satisfaction group, medium satisfaction group, and high satisfaction group. The means values of these groups were compared by t-test. Results showed that there are significant differences of the means values of interpersonal constraints between low satisfaction group and high satisfaction group. This suggests positive interpersonal relationship especially good family member relationship reduce not only job stress but also travel constraints of casino employees. Interestingly, results of t-test showed there is not a significant difference of the means values of structural constraints between low satisfaction group and high satisfaction group. This suggests structural constraints are outside variables which may be related with tourism destination marketing. Destination marketing organizations (DMO) need use all kinds of tools and techniques to promote their tourism destinations so as to reduce structural constraints of casino employees. This research is significant for both theoretical and practical fields. From the theoretical perspective, the study found the internal relationship between travel constraints, job stress, and job satisfaction and the different roles of three dimensions of travel constraints. From the practical perspective, the study provides useful methods to reduce travel constraints and job stress, therefore, raise job satisfaction of casino employees.

Keywords: hotel, job satisfaction, job stress, travel constraints

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Authors: Akhtar Nawaz, Sahar Noor, Iftikhar Hussain

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This paper considers advanced hybrid manufacturing planning both push and pull system in which each customer order has a due date by demand forecast and customer orders. We present a tool for model for tool development that requires an absolute due dates and customer orders in a manufacturing supply chain. It is vital for the manufacturing companies to face the problem of variations in demands, increase in varieties by maintaining safety stock and to minimize components obsolescence and uselessness. High inventory cost and low delivery lead time is expected in push type of system and on contrary high delivery lead time and low inventory cost is predicted in the pull type. For this tool for model we need an MRP system for the push and pull environment and control of inventories in push parts and lead time in the pull part. To retain process data quickly, completely and to improve responsiveness and minimize inventory cost, a tool is required to deal with the high product variance and short cycle parts. In practice, planning and scheduling are interrelated and should be solved simultaneously with supply chain to ensure that the due dates of customer orders are met. The proposed tool for model considers alternative process plans for job types, with precedence constraints for job operations. Such a tool for model has not been treated in the literature. To solve the model, tool was developed, so a new technique was required to deal with the issue of high product variance and short life cycles in assemble to order.

Keywords: hybrid manufacturing system, supply chain system, make to order, make to stock, assemble to order

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Authors: Jeaha Yang, Ahmed Khan, Donna L. Rodela, Mohammed A. Qaudeer

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Traditional supply chain silos still exist today due to the difficulty of establishing trust between various partners and technological barriers across industries. Companies lose opportunities and revenue and inadvertently make poor business decisions resulting in further challenges. Blockchain technology can bring a new level of transparency through sharing information with a distributed ledger in a decentralized manner that creates a basis of trust for business. Blockchain is a loosely coupled, hub-style communication network in which trading partners can work indirectly with each other for simpler integration, but they work together through the orchestration of their supply chain operations under a coherent process that is developed jointly. A Blockchain increases efficiencies, lowers costs, and improves interoperability to strengthen and automate the supply chain management process while all partners share the risk. Blockchain ledger is built to track inventory lifecycle for supply chain transparency and keeps a journal of inventory movement for real-time reconciliation. State design patterns are used to capture the life cycle (behavior) of inventory management as a state machine for a common, transparent and coherent process which creates an opportunity for trading partners to become more responsive in terms of changes or improvements in process, reconcile discrepancies, and comply with internal governance and external regulations. It enables end-to-end, inter-company visibility at the unit level for more accurate demand planning with better insight into order fulfillment and replenishment.

Keywords: supply chain management, inventory trace-ability, perpetual inventory system, inventory lifecycle, blockchain, inventory consignment, supply chain transparency, digital thread, demand planning, hyper ledger fabric

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Authors: Lichung Jen, Yi Chun Liu, Kuan-Wei Lee

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Fruitful data has been accumulated in database nowadays and is commonly used as support for decision-making. In the healthcare industry, hospital, for instance, ordering pharmacy inventory is one of the key decision. With large drug inventory, the current cost increases and its expiration dates might lead to future issue, such as drug disposal and recycle. In contrast, underestimating demand of the pharmacy inventory, particularly standing drugs, affects the medical treatment and possibly hospital reputation. Prescription behaviour of hospital physicians is one of the critical factor influencing this decision, particularly irregular prescription behaviour. If a drug’s usage amount in the month is irregular and less than the regular usage, it may cause the trend of subsequent stockpiling. On the contrary, if a drug has been prescribed often than expected, it may result in insufficient inventory. We proposed a hierarchical Bayesian mixture model with two components to identify physicians’ regular/irregular prescription patterns with probabilities. Heterogeneity of hospital is considered in our proposed hierarchical Bayes model. The result suggested that modeling the prescription patterns of physician is beneficial for estimating the order quantity of medication and pharmacy inventory management of the hospital. Managerial implication and future research are discussed.

Keywords: hierarchical Bayesian model, poission mixture model, medicines prescription behavior, irregular behavior

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Authors: Sadegh Abebi

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There are problems with estimating time of product process of products, especially when there is variable serving time, like control stage. These problems will cause overestimation of process time. Layout constraints, reworking constraints and inflexible product schedule in multi product lines, needs a precise planning to reduce volume in particular situation of line stock. In this article, by analyzing real queue systems with layout constraints and by using concepts and principles of Markov chain in queue theory, a hybrid model has been presented. This model can be a base to assess queue systems with probable parameters of service. Here by presenting a case study, the proposed model will be described. so, production lines of a home application manufacturer will be analyzed.

Keywords: Queuing theory, Markov Chain, layout, line balance

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Authors: Ali Akber Jaffri, Asad Naseem, Javeria Khan, Zubair Hamza, Ishtiaq

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The purpose of this study is to determine safety stock, maximum inventory level, reordering point, and reordering quantity by rearranging lot sizes for supplier and customer in MRO (maintenance repair operations) warehouse of Engro Polymers & Chemicals. To achieve the aim, physical analysis method and excel commands were carried out to elicit the customer and supplier data provided by the company. Initially, we rearranged the current lot sizes and MOUs (measure of units) in SAP software. Due to change in lot sizes, we have to determine the new quantities for safety stock, maximum inventory, reordering point and reordering quantity as per company's demand. By proposed system, we saved extra cost in terms of reducing time of receiving from vendor and in issuance to customer, ease of material handling in MRO warehouse and also reduce human efforts.

Keywords: maintenance repair operation, maximum inventory, reorder quantity, safety stock

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Authors: Chayanika Rout, Debjani Chakraborty, Adrijit Goswami

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Our work presents an inventory model which illustrates imperfect production and imperfect inspection processes for deteriorating items. A cost-minimizing model is studied considering two types of inspection errors, namely, Type I error of falsely screening out a proportion of non-defects, thereby passing them on for rework and Type II error of falsely not screening out a proportion of defects, thus selling those to customers which incurs a penalty cost. The screened items are reworked; however, no returns are entertained due to deteriorating nature of the items. In more practical situations, certain parameters such as the demand rate and the deterioration rate of inventory cannot be accurately determined, and therefore, they are assumed to be triangular fuzzy numbers in our model. We calculate the optimal lot size that must be produced in order to minimize the total inventory cost for both the crisp and the fuzzy models. A numerical example is also considered to exemplify the procedure which is followed by the analysis of sensitivity of various parameters on the decision variable and the objective function.

Keywords: deteriorating items, EPQ, imperfect quality, rework, type I and type II inspection errors

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Authors: Amit Gupta, Deepak Juneja, Sorabh Gupta

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This paper presents a model based on distance based approach (DBA) method employed for evaluation, selection, and ranking of replenishment policies for a single location inventory, which hitherto not developed in the literature. This work recognizes the significance of the selection problem, identifies the selection criteria, the relative importance of selection criteria for this research problem. The developed model is capable of comparing any number of alternate inventory policies for various selection criteria where cardinal values are assigned as a rating to alternate inventory polices for selection criteria and weights of selection criteria. The illustrated example demonstrates the model and presents the result in terms of ranking of replenishment policies.

Keywords: DBA, ranking, replenishment policies, selection criteria

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Authors: Lamia Bouzgarrou, Amira Omrane, Naima Bouatay, Chaima Harrathi, Samia Machroughl, Ahmed Mhalla

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Background and Aims: Professionals of health care sector are exposed to psychosocial constraints like stress, harassment, violence, which can lead to many mental health problems such as, depression, addictive behavior, and burn-out. Moreover, it’s well established that caregivers affected to intensive care units are more likely to experience such constraints and mental health problems. For these caregivers, the mental health state may affect care quality and patient’s safety. This study aims either to identify occupational psychosocial constraints and their mental health consequences among paramedical and medical caregivers affected to intensive units in Tunisian public hospital. Methods: An exhaustive three months cross-sectional study conducted among medical and paramedical staffs of intensive care units in three Tunisian university hospitals. After informed consent collection, we evaluated work-related stress, workplace harassment, depression, anxious troubles, addictive behavior, and self-esteems through an anonymous self-completed inquiry form. Five validated questionnaires and scales were included in this form: Karasek's Job Content Questionnaire, Negative Acts Questionnaire, Rosenberg, Beck depression inventory and Hamilton Anxiety scale. Results: We included 129 intensive unit caregivers; with a mean age of 36.1 ± 1.1 years and a sex ratio of 0.58. Among these caregivers, 30% were specialist or under-specialization doctors. The average seniority in the intensive care was 6.1 ± 1.2 (extremes=1 to 40 years). Atypical working schedules were noted among 36.7% of the subjects with an imposed choice in 52.4% of cases. During the last 12 months preceding the survey, 51.7% of care workers were absent from work because of a health problem with stops exceeding 15 days in 11.7%. Job strain was objective among 15% of caregivers and 38.33% of them were victims of moral harassment. A low or very low self-esteem was noted among 40% of respondents. Moreover, active smoking was reported by 20% subjects, alcohol consumption by 13.3% and psychotropic substance use by 1.7% of them. According to Beck inventory and Hamilton Anxiety scale, we concluded that 61.7% of intensive care providers were depressed, with 'severe' depression in 13.3% of cases and 49.9% of them present anxious disorders. Multivariate analysis objective that, job strain was correlated with young age (p=0.005) and shorter work seniority (p=0.001). Workplace and moral harassment was more prevalent among females (p=0.009), under-specialization doctor (p=0.021), those affected to atypical schedules (p=0.008). Concerning depression, it was more prevalent among staff in job strain situation (p = 0.004), among smokers caregivers (p = 0.048), and those with no leisure activity (p < 0.001). Anxious disorders were positively correlated to chronic diseases history (p = 0.001) and work-bullying exposure (p = 0.004). Conclusions: Our findings reflected a high frequency of caregivers who are under stress at work and those who are victims of moral harassment. These health professionals were at increased risk for developing psychiatric illness such depressive and anxious disorders and addictive behavior. Our results suggest the necessity of preventive strategies of occupational psychosocial constraints in order to preserve professional’s mental health and maximize patient safety and quality of care.

Keywords: health care sector, intensive care units, mental health, psychosocial constraints

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Authors: Mubarak Alhajri

Abstract:

This paper addresses certain inherent limitations of local priority hysteresis switching logic. Our main result establishes that under persistent excitation assumption, it is possible to relax constraints requiring strict positivity of local priority and hysteresis switching constants. Relaxing these constraints allows the adaptive system to reach optimality which implies the performance improvement. The unconstrained local priority hysteresis switching logic is examined and conditions for global convergence are derived.

Keywords: adaptive control, convergence, hysteresis constant, hysteresis switching

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Authors: Akash Verma, Sujit Kumar Samanta

Abstract:

This study examines a discrete-time Geo/G/1 queueing-inventory system attached with (s, Q) inventory policy. Assume that the customers follow the Bernoulli process on arrival. Each customer demands a single item with arbitrarily distributed service time. The inventory is replenished by an outside supplier, and the lead time for the replenishment is determined by a geometric distribution. There is a single server and infinite waiting space in this facility. Demands must wait in the specified waiting area during a stock-out period. The customers are served on a first-come-first-served basis. With the help of the embedded Markov chain technique, we determine the joint probability distributions of the number of customers in the system and the number of items in stock at the post-departure epoch using the Matrix Analytic approach. We relate the system length distribution at post-departure and outside observer's epochs to determine the joint probability distribution at the outside observer's epoch. We use probability distributions at random epochs to determine the waiting time distribution. We obtain the performance measures to construct the cost function. The optimum values of the order quantity and reordering point are found numerically for the variety of model parameters.

Keywords: discrete-time queueing inventory model, matrix analytic method, waiting-time analysis, cost optimization

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Authors: Mohammed Al-Khadher

Abstract:

Currently, we are witnessing rapid advancements in the field of information and communications technology, forcing us, as psychologists, to combat the psychological and social effects of such developments. It also drives us to continually look for the development and preparation of measurement tools compatible with the changes brought about by the digital revolution. In this context, the current study aimed to identify the factor analysis of the Smartphone Addiction Inventory (SPAI) in the Republic of Yemen. The sample consisted of (1920) university students (1136 males and 784 females) who answered the inventory, and the data was analyzed using the statistical software (AMOS V25). The factor analysis results showed a goodness-of-fit of the data five-factor model with excellent indicators, as RMSEA-(.052), CFI-(.910), GFI-(.931), AGFI-(.915), TLI-(.897), NFI-(.895), RFI-(.880), and RMR-(.032). All within the ideal range to prove the model's fit of the scale’s factor analysis. The confirmatory factor analysis results showed factor loading in (4) items on (Time Spent), (4) items on (Compulsivity), (8) items on (Daily Life Interference), (5) items on (Craving), and (3) items on (Sleep interference); and all standard values of factor loading were statistically significant at the significance level (>.001).

Keywords: smartphone addiction inventory (SPAI), confirmatory factor analysis (CFA), yemeni students, people at risk of smartphone addiction

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Authors: Saeed Poormoaied, Zumbul Atan

Abstract:

Emergency shipments provide a powerful mechanism to alleviate the risk of imminent stock-outs and can result in substantial benefits in an inventory system. Customer satisfaction and high service level are immediate consequences of utilizing emergency shipments. In this paper, we consider a single-echelon periodic review inventory system consisting of a single local warehouse, being replenished from a central warehouse with ample capacity in an infinite horizon setting. Since the structure of the optimal policy appears to be complicated, we analyze this problem under an order-up-to-S inventory control policy framework, the (S, T) policy, with the emergency shipment consideration. In each period of the periodic review policy, there is a single opportunity at any point of time for the emergency shipment so that in case of stock-outs, an emergency shipment is requested. The goal is to determine the timing and amount of the emergency shipment during a period (emergency shipment policy) as well as the base stock periodic review policy parameters (replenishment policy). We show that how taking advantage of having an emergency shipment during periods improves the performance of the classical (S, T) policy, especially when fixed and unit emergency shipment costs are small. Investigating the structure of the objective function, we develop an exact algorithm for finding the optimal solution. We also provide a heuristic and an approximation algorithm for the periodic review inventory system problem. The experimental analyses indicate that the heuristic algorithm is computationally more efficient than the approximation algorithm, but in terms of the solution efficiency, the approximation algorithm performs very well. We achieve up to 13% cost savings in the (S, T) policy if we apply the proposed emergency shipment policy. Moreover, our computational results reveal that the approximated solution is often within 0.21% of the globally optimal solution.

Keywords: emergency shipment, inventory, periodic review policy, approximation algorithm.

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