Perfect Items Research Articles

A sustainable manufacturing–remanufacturing inventory model with price and green sensitive demand for defective and usable items

A sustainable manufacturing–remanufacturing inventory model with two production phases is presented in this study. In this two phases model, the first phase is used for manufacturing whereas the second phase is used for both manufacturing and remanufacturing. Keeping in mind about environment and price of products, it is presumed that market demand rate is influenced by the greenness of item and unit selling price simultaneously. Remanufacturing is performed for non-serviceable items i.e., defective items which are produced from imperfect production and used items that are purchased from the market. But the products for which remanufacturing cost is more than manufacturing cost are scraped off. In the production process carbon releases from setting up, manufacture and holding of the perfect items. To mitigate the carbon emission carbon tax regulation is imposed. Next, concavity of the profit function is driven through the pseudo concavity. Profit is maximized by minimizing the economic, environmental, and social effect. The models are illustrated by a numerical example and a sensitivity analysis is also elaborated for fixed parameters. Special cases are provided to compare the result with previous literature. The results shows that manufacturer wishes to engage in remanufacturing as remanufacturing cost continuously increases with respect time. Another important finding is that the manufacturer can choose remanufacturing as the cost is lower than manufacturing for saving environment. Finally, mathematical findings are listed and managerial implications are recorded.

An Inventory Model for Growing Items When the Demand Is Price Sensitive with Imperfect Quality, Inspection Errors, Carbon Emissions, and Planned Backorders

Inventory models that consider environmental and quality concerns have received some attention in the literature, yet no model developed to date has investigated these features in combination with growing items. Therefore, there is a need to incorporate these three relevant aspects together in a single inventory model to support decisions, compare results, and obtain new knowledge for the complexities of the real world. Moreover, current sustainable inventory management practices aim at mitigating the ecological consequences of an industry while preserving its profitability. The present study aligns with this perspective and introduces an economic order quantity (EOQ) model that considers imperfect quality while also accounting for sustainability principles. More specifically, the model addresses growing items, which have a demand dependent on selling price and the unique ability to grow while being stored in inventory. Additionally, the analysis acknowledges the possibility of classification errors during the inspection process, encompassing both Type-I and Type-II inspection errors. Furthermore, the model permits shortages and ensures that any shortage is completely fulfilled through backorders. The optimization model produces an optimal solution for the proposed model that is derived by optimizing three decision variables: order quantity of newborn items, backordering quantity, and the selling price of perfect items. A numerical example is presented, and the results are discussed. Finally, a sensitivity analysis on variations of parameters such as Type-I and Type-II errors shows that it is advantageous to reduce the percentage of good items that are misclassified as defective (i.e., Type-I error). As there is a direct impact of such errors on sales, it is imperative to address and mitigate this issue. When defective items are mistakenly classified as good Type-II errors, adverse consequences ensue, including a heightened rate of product returns. This, in turn, results in additional costs for the company, such as penalties and diminished customer confidence. Hence, the findings clearly suggest that the presence of Type-I and Type-II errors has a negative effect on the ordering policy and on the total expected profit. Moreover, this work provides a model that can be used with any growing item (including plants), so the decision-maker has the opportunity to analyze a wide variety of scenarios.

Reduction of makespan through flexible production and remanufacturing to maintain the multi-stage automated complex production system

Multi-stage production systems have been increasingly popular with a smart production system that has automated and flexible production rates. However, due to the complex structure of such a production system, most studies approach this as a single-stage production system or multi-stage by only incorporating a minimum number of real features. Thus motivated, this study presents the importance of automation and flexibility to reduce the makespan for multi-stage work-in-process inventory under a complex production system. This is a pioneer study in reducing the makespan for flexible multi-stage production systems since each stage of production produces defective items and the former stage’s production is required to finish before running the latter stage. We consider the automated multi-stage production system and aim to reduce makespan duration by optimally controlling the amount of production lot, production, and backorder rate. In this system, finished products are obtained in the last stage, and in each stage, there are defective items. To mitigate defective items, the production system has a remanufacturing process in each stage, in parallel with production, such that the makespan does not increase and defective products of that stage are transferred to perfect items. This study characterizes the optimal lot size, production rate, and backorder rate at each stage along with the optimal selling price to maximize the total profit of the system. In analyzing the production model, we use a classical optimization method. We also conducted numerical experiments to validate the model and performed a sensitivity analysis of key parameters to derive several managerial insights on the impacts of optimized backorder rate and lot sizing on the profit. The results show that a significant reduction of defective items as waste reduction can be achieved by the reduction of makespan that utilizes a flexible production rate and remanufacturing rate. Our results also show that the benefit of flexible production instead of traditional production is 11.48% and the benefits of variable backorder for multi-stage instead of fixed and no-backorder are 93.62% and 99.55%, respectively.

An imperfect production-inventory model for reworked items with advertisement, time and price dependent demand for non-instantaneous deteriorating item using genetic algorithm

This article deals with an imperfect production inventory system with advertisement, price, and time-dependent demand for a non-instantaneous deteriorating item. Every manufacturing company aims to produce only perfect quality items, but this is not possible in reality. Firstly, the manufacturing system starts producing perfect items, but after some time, it starts producing imperfect items also, because of the manufacturing machine's long run. Perfect products are ready to sell, and some percentages of imperfect products are reworked to become perfect, and the remaining defective products are sold at a cheaper price. An efficiency cost is included to maintain the system efficiency. Considering these conditions, we developed a profit function. This profit function is highly nonlinear. Therefore, we employed a real coded genetic algorithm to obtain the optimum values of production rate, selling price of the perfect quality item, selling price of imperfect item, and inverse efficiency factor to maximise the profit. The model is demonstrated by using numerical example followed by sensitivity analysis.

A Fuzzy Imperfect Production Inventory Model Based on Fuzzy Differential and Fuzzy Integral Method

In the inventory theory, to treat the uncertainty, the fuzzy set concept is used in order to provide a feasible approach to deal with the uncertainty problem. In this research work, a fuzzy economic production quantity model with interactive fuzzy demands is proposed. In a production process, in the beginning, the system is assumed to be in a controlled state in which only perfect items are manufactured. Later, the manufacturing production process shifts to be an out-of-control-state system; producing both perfect and imperfect items simultaneously, this is considered as a fuzzy state. The defective production rate is also taken into account as a fuzzy state. Here, the selection process of produced items is realized during the production period. With the aim of studying the practical feasibility of the fuzzy economic production inventory model along with a sensitivity analysis of some parameters, different numerical examples are illustrated.

Strategic decisions in an imperfect quality and inspection scenario under two-stage credit financing with order overlapping approach

To sustain fierce competition prevailing in the market, customer satisfaction is one metric that any firm can profoundly rely on to measure its performance. In the proposed model, a tri-tier supply chain (manufacturer - wholesaler - retailer) is studied where the consignment received is unreliable due to imperfect items. With the focus on customer satisfaction, the consignment is first screened for defects where screening, realistically, is error prone. With the intent of not losing customers due to shortages, the demand during current screening period is fulfilled from the perfect items of the previous order cycle. In addition, for financial safety, the wholesaler who receives a full trade credit by the manufacturer in turn offers partial a trade credit to his/her subsequent retailer. Therefore, a valid assumption in such type of scenario is that the demand is credit period dependent. Considering all the above-mentioned factors, an optimal replenishment policy has been investigated which serves as a ready reckoner for the operations manager. An extensive numerical and sensitivity analysis has been performed to demonstrate the validity of the proposed framework and provide useful managerial insights.

Flexible inventory system of imperfect production under deterioration and inflation

This study emphasizes the development of a flexible inventory system considering rework requirements on imperfect and defective items. This work has considered defective items could be sold at a lower price in the market as compared to the perfect items. The developed model has considered Weibull deterioration and inflation to balance the same amount in the future due to its potential earning capacity. And demand's function depends on price as well as inventory level because a large pile of goods and their price strategy attracts more customers to generate higher demand. The work also supports managerial decision-making by focusing on the volume flexibility system for smooth production runs. The mathematical formulation of the developed inventory system tries to optimize the inventory cost function under a realistic scenario. A solution procedure has been illustrated and assisted with a numerical example. Later, a validation test is also performed to check the robustness of the proposed mathematical model. The findings of the study will support policymakers, strategists, and firms to implement flexible inventory systems under realistic conditions.

Nonlinear pentagonal intuitionistic fuzzy number and its application in EPQ model under learning and forgetting

In this current era, the concept of nonlinearity plays an important and essential role in intuitionistic fuzzy arena. This article portrays an impression of different representation of nonlinear pentagonal intuitionistic fuzzy number (PIFN) and its classification under different scenarios. A new de-intuitification technique of non-linear PIFN is addressed in this article along with its various graphical representations. Additionally, in this paper, we have observed this by applying it in an economic production quantity model where the production is not perfect and defective items are produced which are reworked. The model is considered under learning and forgetting, where learning is considered as linear, nonlinear PIFN and crisps arena. It is observed from the numerical study that high learning effects in rework lead to decrease in production of defective item, which, besides an economic advantage, may have a positive effect on the environment. Even though forgetting has an adverse effect, the average total cost is much less than that of the basic model which ignores worker learning and forgetting. Finally, comparative and sensitivity analysis result shows the utility of this noble work.

An Investigation of a Supply Chain Model for Co-Ordination of Finished Products and Raw Materials in a Production System under Different Situations

In the production system, the production of a perfect item is essential for existing competitive market situations. To produce a perfect finished product, the quality of a raw material is a crucial issue of a production system. This paper has examined this issue with an insightful production-inventory model of the manufacturer of a deteriorating item selling goods to multiple markets with different selling seasons. We have provided an answer strategy to track down the optimal production plan for raw materials and the ideal creation plan for completed items. Transportation cost was incorporated for transporting the raw material. Marketing of the finished product is another crucial factor for selling products and earning revenues. The main objective of the present study is to adopt a production model in inventory for inferring request capacities for multi-item, multi-outlet circumstances. As of late, much accentuation has been given to the consideration of the control and support of creation inventories of disintegrating things. The demand rate is persistent and holding cost is a direct function of time. This paper has followed an analytical approach to diminish the entire inventory cost. Finally, a sensitivity analysis was performed to study the effect of changes of different parameters of the model on the optimal policy. Moreover, in order to approve the determined models, we have clarified mathematical models and examined affectability.

Two-plant production model with customers’ demand dependent on warranty period of the product and carbon emission level of the manufacturer via different meta-heuristic algorithms

In the developed countries, most of the customers are aware about the harmful effects of purchased products that pollute the environment. On the other hand, the aim of the manufacturer is to reduce by controlling the pollution rates. Motivating from this situation, a two-plant production model in single manufacturing system with warranty period of the product and carbon emission level dependent demand is developed. The manufacturer inspects every produced item in both plants before sending it to the market. After inspection, a part of imperfect items is reworked to reproduce these items into perfect items and also to reduce the loss of the manufacturer. The objective of the model is to determine the optimal values of the product’s warranty period and the production period in each plant in order to maximize the average profit of the manufacturer subject to some constraints. To illustrate and validate the model, two numerical examples are considered and solved by four meta-heuristic algorithms. Finally, to examine the effects of some significant model parameters on the optimal policy, sensitivity analyses are performed.

Defective and Repairable Items Unsteady Deterioration Rate Inventory Model Under Three Tired Prices and Time Dependent Demand

Lot received or units produced are not all perfect items. A time and price dependent demand inventory model is formulated when items produced or lot received are of defective and repairable nature. Three tired pricing is considered. For different situations, expression for total profit is derived to derive optimal solution. For parameter, post-optimality computations are also done.

Production Inventory Model under Time Dependent Demand, Uneven Manufacturing Rate and Manufacture Time Dependent Selling Price

In this paper, an inventory model for production of a single article with an uneven manufacturing rate and manufacturing time subsidiary selling cost has been considered. The considered production inventory model is accepted to create perfect items in beginning however because of different elements, after some time the production begins diminishing exponentially with time, i.e., the variable production rate has been thought of. The demand is time subordinate. Initially up to certain time, production rate remains constant. But after some time, due to various factors, production will decrease. Therefore, the efficiency (E) of such factors must be increased to get more production which can maintain the production efficiency cost which has been applied. Considering this fact inverse efficiency λ has been introduced in production rate. By utilizing differential calculus, expected maximum profit has been resolved. The goal of the examination is to decide the ideal arrangement for a production framework that expands the total benefit subject to certain limitations viable. Results are examined by means of a mathematical example to outline the hypothesis.

Single-manufacturer and multi-retailer supply chain model with pre-payment based partial free transportation

In this paper, a supply chain model between a manufacturing firm and a group of retailers has been developed. Manufacturing firm produces simultaneously both perfect and imperfect items which are separated by screening process. Then the perfect items are transferred to the retailers’ showroom/warehouse located in different places and a part of imperfect items are repaired by rework process. Retailers receive the products from the manufacturer with paying partial pre-payment to ensure the replenishment of order. On the other hand, the manufacturer provides partial free transportation facility to the retailers due to pre-payment. The corresponding problem has been formulated mathematically as a profit maximization problem and then solved it analytically. As an illustration of this supply chain model, three numerical examples have been considered and solved. Finally, post optimality analyses have been carried out to investigate the effects of changes of different parameters on the optimal policy.

Multi-item single-source production quantity model for imperfect items with rework failure, inspection errors, scraps, and backordering

This paper represents a multi-item single-source (MISS) production quantity model for random imperfect items with repair failure, inspection errors, sales return, scraps, and backordering. In this study, it is assumed that some manufactured/produced goods might not be without fault and the first phase of inspection over the quality of goods might make some inspection errors through the classifying of imperfect/defective and perfect items. Besides, this model contains one or more steps of separation procedure that is after the rework time and there is no screening error in this period (i.e., error-free). The purpose of this investigation is to obtain the optimum cycle length and the optimal backordered quantity for each item to minimalise the total expected value cost. Finally, the numerical example is illustrated to explain and solve the studied model using our investigated innovative methodology, which is additionally clarified and explained over a sensitivity analysis.

An inventory model for deteriorating items with imperfect quality under advance payment policy

In the business world, it is generally observed that the supplier gives cash discount due to advance payment. The buyer may either pay off the total purchase cost or a fraction of the total purchase cost before receiving the products. If the buyer makes full payment then he receives a cash discount instantly. If the buyer pays a fraction of the total purchase cost, then (s)he receives the cash discount while paying the remaining amount at the time of receiving the lot. Moreover, in most of the inventory models, it is generally assumed that the delivered lot contains only perfect items. But in reality, presence of imperfect items in the received lot cannot be overlooked as it will affect total profit of the system. Thus, the study of inventory models considering the presence of imperfect items in the lot makes the model more realistic and, it has received much attention from inventory managers. This paper develops a model that jointly considers imperfect quality items and the concept of advance payment scheme (full and partial). The objective is to determine optimal ordering quantity in order to maximise the total profit of the system. The necessary theoretical results showing the existence of global maximum is derived. The model is illustrated with the help of numerical examples, and sensitivity analysis is carried out on some important system parameters to see the effects on the total profit of the system. The study shows that full advance payment scheme is beneficial for the buyer.

The Perfection Premium

This research documents a perfection premium in evaluative judgments wherein individuals disproportionately reward perfection on an attribute compared to near-perfect values on the same attribute. For example, individuals consider a student who earns a perfect score of 36 on the American College Test to be more intelligent than a student who earns a near-perfect 35, and this difference in perceived intelligence is significantly greater than the difference between students whose scores are 35 versus 34. The authors also show that the perfection premium occurs because people spontaneously place perfect items into a separate mental category than other items. As a result of this categorization process, the perceived evaluative distance between perfect and near-perfect items is exaggerated. Four experiments provide evidence in favor of the perfection premium and support for the proposed underlying mechanism in both social cognition and decision-making contexts.

Ergonomic Analysis of an Integrated Human Factor Assessment and Simulation in a Workplace Design

Currently, the expanded multifaceted nature of items and assembling forms presents world-class manufacturers with time to market and resource improvement challenges. Assembling Engineering Teams are expected to empower perfect new item dispatches and hold fast to cost, quality and beginning of creation targets. To address these difficulties, driving makers influence their authoritative knowledge and the accessibility of 3D models of items and assets to practically approve their assembling forms forthright. With new advancing innovation, a large number of approval investigations can be directed productively and naturally to guarantee forthright creation advancement. A definitive objective of office ergonomics is to make the working station appropriate for the laborer and all the laborers with the adaptability to get most extreme profitability and productivity. This paper proposes an appraisal of a workplace design and ergonomics analysis based on simulation. Therefore, is possible to solve ergonomic risk in the workplace design.

Autonomation policy to control work-in-process inventory in a smart production system

The necessity of optimum safety stock is really essential for any smart production system. For this reason, the effect of autonomation policy makes a big difference with the basic traditional automation policy. Basically, for a long-run production system, a process may transfer to an ‘out-of-control’ state from an ‘in-control’ state due to labour problems, machinery problems, or any kind of energy problems. During this ‘out-of-control’ state, machines produced imperfect items instead of perfect items. As a result, an inspection is required to identify the imperfect ones. Until now, this inspection has been utilised by human beings through the traditional automation policy and inspection errors may occur. To perform an error-free inspection, an autonomation policy is examined in this model to detect imperfect items from the production process, which makes the process smarter. The defective rate is random and follows a certain distribution. A budget and a space constraints are adopted, which makes the model non-linear with a constraint problem. Contradictory to the existing literature, the demand is price- and quality-sensitive together in a smart production system. To solve this non-linear problem with an optimised value of backorders, number of delivery lots, safety factors, and collection rate, a non-linear optimisation technique (Khun–Tucker optimisation technique) is employed. A numerical example and sensitivity analysis are provided to illustrate the model. The result finds that the optimum autonomation policy can save work-in-process inventory at the optimum value of the decision variable in the proposed model.

An Optimal Production Policy Model Considering Defective Items in the Context of Carbon Tax Scheme

Carbon tax scheme is one main low-carbon policy to curb carbon emission. This paper develops an optimal production policy model with defective items in a single production period under carbon tax scheme. We assume that the demand for perfect items is price-sensitive and environment-sensitive and the defective items can always be sold. Firstly, we get the optimal production policy and the maximum expected profit. Secondly, we analyze the effect of some parameters emphatically and the results show that when the tax rate is low, firm can’t utilize the optimal production policy unless the rate of perfect product is high. We also find that the optimal production lots may increases when the rate of perfect product increases and the profit may decreases in the same situation, which is inconsistent with intuition.

A deterministic production inventory model with defective items, imperfect rework process and shortages backordered

The basic assumption of the conventional inventory models is that all items produced are of perfect quality. In practice, some defective items are produced due to process deterioration or other factors. This paper develops a mathematical model for an imperfect production inventory system. It is assumed that the defective items produced in the regular production process consist of scrap, imperfect quality and reworkable items. The rework process is accomplished immediately when the regular production process ends, and the rework process produces scrap, imperfect quality and as-good-as perfect items. A numerical example is provided to illustrate the developed model, and a sensitivity analysis is carried out. It was found that producing scrap and imperfect quality items through the reworking is crucial, since this assumption effects optimal policy. Managerial insights are also presented based on the numerical examples.