Imperfect Production Process Research Articles

Does outsourcing enhance consumer services and profitability of a dual-channel retailing?

In the era of digital commerce, the concept of dual-channel retailing has attracted increased attention. Dual-channel retailing increases the importance of outsourcing for an imperfect production process to enhance customer satisfaction. This study explores a sustainable dual-channel retailing strategies for an imperfect production process under a flexible production system. The manufacturer runs a production process prone to defects utilizes both offline and online channels for product sales. The manufacturer contemplates green investments to enhance the production efficiency and reduce waste and carbon emissions, alongside the possibility of outsourcing a portion of production to a partner. A mathematical model is developed to accounts for these factors and analyzes the optimal allocation of products between channels, pricing strategies, production rates, and investments amount to reduce carbon emissions. The model incorporates demand sensitiveness to green practices and channel's selling price. Results of this research are directed towards offering significant perspectives for organizations that aspire to attain a harmonious equilibrium among financial profitability, ecological sustainability, and addressing deficiencies in their manufacturing procedures in a dual-channel retail setting through subcontracting. Numerical illustrations exhibit that partial outsourcing enhances system's profit by 2.03%, whereas investments to reduce carbon emissions enhance the profit by 4.95%. Flexibility in the production process helps to increase the profit by 13.50%, and channel coordination helps to enhance the profit by 38.54%.

Optimal Pricing and Retailing Strategy for an Assembled Product Manufacturing–Remanufacturing Process under Carbon Emission Regulations and Autonomation

Online-to-offline (O2O) retailing offers unique opportunities for customizable assembled products with spare parts. Customers can browse and configure their desired product online, selecting from various components. Imperfect production, where a certain percentage of products have defects, can be amplified in the manufacturing system. Stricter carbon emission regulations put pressure on manufacturers to minimize waste. This creates a tension between discarding imperfect products, generating emissions, and potentially offering them at a discount through the O2O channel, which could raise quality concerns for consumers. In this study, an imperfect single-stage production process is examined, incorporating manufacturing–remanufacturing within a single stage for assembled products containing various spare parts. The study explores an investment scenario aimed at enhancing the environmental sustainability of the product. Additionally, two carbon emissions regulation strategies, specifically carbon cap-and-trade regulation and carbon taxation, are evaluated for their effectiveness in mitigating carbon footprints. The identification of waste, particularly in the form of defective items, is achieved through automated inspection techniques. The demand for spare parts associated with the assembled products is intricately linked to the selling prices set across diverse channels. Finally, the total profit of the manufacturing system is maximized with the optimized value of the selling prices, order quantity, backorder quantity, and investments in autonomated inspection, setup cost, and green technology. Numerical illustrations show that system profit was optimized when the defective rate followed a triangular distribution under carbon cap-and-trade regulation and when green technology investment helped to enhance retailer profit by 18.12%, whereas autonomated inspection increased retailer profit by 10.27%.

The economic production quantity model for an imperfect production process by control chart design

The Economic Production Quantity (EPQ) plays a crucial role in the manufacturing process. The traditional EPQ model operates under the assumption that Non-Conforming (NC) items are not produced, and the process remains under control. However, real-world scenarios often involve the production of NC products, leading to process deviations. This study introduces a model that optimizes the design of a control chart to incorporate NC products into the EPQ model. The model integrates inventory and quality-related costs to minimize the expected total cost by determining EPQ, sample size, and control limit. The solution methodology employs direct search techniques to solve this problem. The sensitivity analysis results demonstrate the significant cost reduction achieved by the proposed model compared to the classical EPQ model. The numerical examples presented in the study show an average cost reduction of approximately 21 percent, highlighting the potential effectiveness of the model in cost reduction efforts.

An Imperfect Production Inventory Model for Instantaneous Deteriorating Items with Preservation Investment Under Inflation on Time Value of Money

Effective inventory management is crucial for businesses dealing with deteriorating items, where demand is influenced not only by traditional factors but also dependent on the selling price. This research paper proposes a comprehensive inventory model that considers the dynamic nature of demand for deteriorating items and incorporates the impact of inflation on the time value of money, all within the context of an imperfect production and screening process. To reduce the waste of products, the proposed model uses a rework process to convert imperfect items into perfect ones. Additionally, this study incorporates preservation technology investment to alleviate the rate of deterioration under partially backlogged shortages. The incorporation of an imperfect production process further enhances the model’s practical applicability by addressing real-world scenarios where production may not always be flawless. The study employs mathematical modeling and optimization techniques to derive optimal ordering policies that balance the conflicting objectives of minimizing costs. To validate the model, numerical analysis has been performed, and the convexity of the total cost function has been shown graphically and analytically using MATHEMATICA software. Sensitivity analyses are conducted to assess the robustness of the proposed model under varying parameters, providing valuable insights for decision-makers.

A flexible planning approach for integrated lot sizing and rework planning with random proportion of defective products

We consider a stochastic capacitated lot sizing problem with in-line rework. Both defective and defect-free products can be the result of an imperfect production process in real-world production systems. However, the proportion of defective items in a production lot is subject to uncertainty. For economic and environmental reasons, the possibility to rework defective products appears reasonable since these products usually have considerable value. In this paper, a nonlinear model formulation for integrated lot sizing and rework planning is proposed. We use a sample average approach to approximate the generic nonlinear model formulation. To cope with the randomness of the proportion of defective products, we apply a flexible planning approach that allows the adjustment of production and rework quantities. We conduct extensive numerical investigations to evaluate the performance of the proposed planning approach.

Benefits of Preservation, Green and Quality Improvement Investment for Waste Management in Sustainable Supply Chain under Fuzzy Learning and Inflation

In the modern world, waste management, incorporating the quality of the products, energy consumption, and environmental concern have become significant challenges for supply chain managers. Also, smart devices are essential for daily life in the current socioeconomic environment, and customers primarily contemplate a smart product’s price and energy usage before purchasing that. In this situation, to maintain a balance between the selling price, energy consumption, and carbon emission from supply chain operations becomes necessary. So this study develops a twoechelon sustainable inventory model for deteriorating items with an imperfect production process under energy consumption and selling price dependent demand. The producer makes a rework process and quality improvement investment to mitigate defective products and enhance the quality of the products. The present model develops under the influence of inflation. Also, preservation and green technologies are used to mitigate the rate of deterioration and carbon emission, respectively. Firstly, the model is created in a crisp sense, and then expanded into a fuzzy learning model to examine the impact of the learning effect in an imprecise environment. A numerical analysis is performed to validate the proposed model, and the cost function’s convexity is shown graphically using mathematica software. The result of the proposed model provides significant insights to decision-makers on how to efficiently reduce waste while still minimizing the total cost of the system by investing in high efficiency preservation, quality improvement and green techniques. Also, due to learning in fuzziness, the fuzzy learning model gives the lowest total cost, followed by the fuzzy and crisp model. Finally, for various parameters, a sensitivity analysis is performed to gather valuable observations and management insights.

Production run time setting by considering time value of money for imperfect production process

Chung and Hou develop an imperfect manufacturing process for obtaining the production run. In this research, we consider the extended problem under time value of money for determining the production run. Taguchi’s concept is adopted as the measurement of performance.

Optimal production run in an imperfect production process with maintenance under warranty and product insurance

Optimal production run in an imperfect production process with maintenance under warranty and product insurance

Effect of green investment to reduce carbon emissions in an imperfect production system

Climate change is a serious hazard to human life today, and the greenhouse effect is its key cause. The production sector is one of the biggest contributors to climate change as it accounts for a large part of greenhouse gas emissions. Many nations have created ecological policies and regulations to prevent industries from emitting excessive amounts of carbon emissions (CO2) into the ecosystem. Industry experts believe that green technology might aid in making a more sustainable future as a result of the current climate crisis. Investments in green technologies are rising rapidly which may allow more nations to adopt green technology and transition away from non-renewable resources. This research explores the viability of investing in green technology to achieve a sustainable production scheduling considering an uncertain amount of CO2 during the processes of production, transport, and storage, and thus offers managerial insights for policymakers to reduce both CO2 and overall cost. This study assumes an imperfect production process where a fraction of the items is faulty, and the firm employs a rework approach to rectify the faulty items. The firm invests in green technology to significantly cut CO2 and support innovation to address the climate crisis and benefit communities. The main point of the study is to develop a solution procedure of the problem associated with the amount of CO2 where all the CO2 factors might increase or decrease fuzziness. According to the skills gained by the decision maker we fuzzify all CO2 factors as trapezoidal fuzzy numbers, and we use a signed distance method to defuzzify the model. The results imply that the production sector’s outsize ecological CO2 can be reduced without compromising quality by designing optimal production strategies. The findings also confirm that green investment is the greatest economical method for reducing CO2 and overall costs.

Fuzzy Inventory Model for Imperfect Items with Price Discount and Penalty Maintenance Cost

The present paper considers the fuzzy economic manufacturing model (FEMM) for an inventory model with an imperfect production process that has been studied along with rework. During the pandemic, it is evident that the products accumulated without a sale, which has increased the maintenance cost of the products. This research paper compares a special sale of products with discount and without discount prices both in the fuzzy environment and in the crisp case. New computing methods based on fuzzy logic are being utilized to enhance identification, decision making, and optimization. A triangular fuzzy number is applied in the economic production quantity to emphasize the importance of optimal manufacturing. The EPQ model’s optimal total cost is obtained in the crisp version. It is to be noted that this model is developed in the fuzzy sense by using the deterioration as a triangular fuzzy number. The applications of this model in the fields are constructing customized industrial machinery or heavy‐duty construction equipment, specific chemicals, and processed food. By using MATLAB R2021, a numerical example of the optimal solution is provided. Finally, the present research discusses how changing several parameters affects the optimum total cost.

Green Integrated Inventory Model of Deteriorating Items with Imperfect Production Process under Inflationary Environment

Green Integrated Inventory Model of Deteriorating Items with Imperfect Production Process under Inflationary Environment

Green integrated inventory model for deteriorating items with imperfect production process under inflationary environment

Green integrated inventory model for deteriorating items with imperfect production process under inflationary environment

A Sustainable Production Scheduling with Backorders under Different Forms of Rework Process and Green Investment

Rework is currently a necessity for businesses and commercial organizations across the world. It is only beneficial in tackling climate change if the process emits less greenhouse gases than would otherwise be emitted. This study designs an optimal production scheduling model to reduce both carbon emissions during the processes of production, transport and storage, and setup cost by leveraging on green technology efforts in an imperfect production process where a fraction of items is erroneous so that the firm may run out of inventory. The producer implements a rework strategy to rectify the flawed products, anda flexible rework rate is offered since the rework might be executed on various schemes. The flexible rework allows the producer to choose therework rate, which can differ from the production rate, as well as the rework process itself, which can be asynchronous or synchronous.The two forms of green investments: quadratic and exponential are considered in the study. The main point of the study is to derive a solution procedure of the various problem settings associated with the rework rate, rework process and green investment. The findings suggest that developing the optimal production schedule (lot-sizes, backorders, setup cost and green investment amount) can lower the manufacturing sector’s excessive ecological carbon emissions. The findings also support the idea that making green investments is the most cost-effective way to cut carbon emissions and setup cost simultaneously.

Joint optimization of production lot-sizing and condition-based maintenance in an imperfect production process with dependent indicators

ABSTRACT This paper addresses the integrated optimization of the economic manufacturing quantity and the condition-based maintenance policy of a deteriorating manufacturing system. The considered facility produces a single type of product and is inspected at the end of each production run. Upon inspection, two dependent indicators are revealed: one implies whether the production process is in control or not and the other one represents the deterioration level of the facility. The dependence between the two indicators is that whenever the facility deterioration exceeds a pre-determined level, the system becomes more vulnerable such that the production process may switch to the out-of-control state. In the out-of-control state, a proportion of defective items is fabricated. Considering the inter-dependencies between production process and machine degradation, this paper develops an integrated production and maintenance model to minimize the overall cost. The expected cost rate in the long run is taken as the objective function to assess the proposed model, where the joint optimization of the lot-sizing and the maintenance policy is developed. The problem is formulated in the context of a semi-Markov decision process and solved with the successive approximation method. A numerical example is given to illustrate the applicability of the proposed model.

A Lot-Sizing Model for a Multi-State System with Deteriorating Items, Variable Production Rate, and Imperfect Quality

Conventional production systems assume that during the manufacturing processes, machines operate without breakdown over an infinite planning horizon and manufacture only products of good quality. Imperfect production processes as a result of machine degradation are common in manufacturing. This paper deals with a problem that concerns the modelling and evaluation of the performance of a multi-state production system that is subject to degradation and its effect on lot sizing. Here, we consider that the cycle starts with a particular production rate until a point when the inventory reaches a certain level after which the failure mode is activated due to the deterioration of certain components, leading to a reduction in the production rate in order to ensure the continuity of supply until the maximum inventory level is reached. Production then stops to restore the machine and the cycle starts again. We have assumed that the rate at which inventory deteriorates is exponential and that demand is constant. A numerical example is used to illustrate the model application, followed by sensitivity analysis. This paper contributes to lot sizing in the area of machine reliability by considering a production system in a degraded state with a non-increasing production rate for deteriorating items with imperfect quality and partial backlogging.

Joint replenishment strategy for deteriorating multi-item through multi-echelon supply chain model with imperfect production under imprecise and inflationary environment

As the industry environment becomes more competitive, the supply chain management for multi items has become an essential part of the industries. In this paper, a multi-echelon inventory model for deteriorating multi items with imperfect production has been developed under the environment of fuzzy and inflation. A single producer, multi-supplier, and multi-retailer are considered from the integrated point of view. Here, the producer only produces the retailer’s need to have a tremendous advantage and minimum loss. It is observed that the inflation rate is almost uncertain for deteriorating goods in every supply chain. In this paper, the inflation rate is taken as a triangular fuzzy number, and the centroid method is used to defuzzify the profit function. The shortage is not allowed in any part, an imperfect production process is considered, but it is not reworkable in this supply chain. Different inflation rates are considered for additional items because inflation has strained the most vulnerable consumers (the daily wage earners), who mainly demand goods in short and small quantities. This entire model is developed based on the retailer’s demand and due to which, the profit potential is maximized. The central premise of this study is to get maximum benefit by creating a production model for deterioration items. Finally, a numerical example and sensitivity analysis illustrate the present study. It is observed that if the number of shipments taken from the supplier increases during the production period, the total profit increases in crisp and fuzzy. If a positive change occurs in the number of shipments received through the producer to the retailer, then the fuzzy model has positive, but a slight negative change occurs in the crisp model. This paper shows the effect of a joint replenishment policy for multi-item compared with the independent approaches.

A cleaner EPQ inventory model involving synchronous and asynchronous rework process with green technology investment

The amount of carbon emission in the atmosphere continues to grow, and production, storage and transportation are major contributors that are repeatedly unnoticed when it comes to solving the problem. A carbon levy and cap EPQ model has been explored in this study for a controlled carbon emission in view of cleaner production under imperfect production processes where a fraction of the products is faulty. The model incorporates emissions from transportation, production, and storage activities, which are meant to be decreased by green investment. The manufacturer employs a rework approach to rectify the faulty products. Flexible rework allows the manufacturer to choose the rework rate, which can differ from the manufacturing rate, as well as the process of rework, which can be asynchronous or synchronous. A linear rework cost function of the rework rate is assumed. We sought to obtain the lowest cost with respect to optimal lot size, and backorder under the effect of controlling carbon emissions by applying the exponential form of green investment. Keeping these in mind, several mathematical models derived for various rework rate and rework process assumptions with the objective emphases on gaining a trade-off between cost and emissions, thereby finding the optimal production-distribution inventory strategy and an appropriate sustainable plan for handling both synchronous and asynchronous rework process. We show a constrained non-linear programme (NLP) and derive a calculus optimization technique to solve it. An iterative solution technique is used to arrive at the optimal decisions, which are shown analytically and numerically. The results validate the impacts of controlled carbon emissions on the production strategies. The findings mainly suggest that increasing the carbon levy reduces emissions. The firm has more options to decrease emissions caused by industrial activity with the help of green technologies. Although green technology has a higher upfront cost, the producer will reap the advantages of lower emissions.

A Vendor-Managed Inventory Model for Imperfect Production Process Using Sustainability Investment and Energy Consumption Under Different Carbon Policies

A Vendor-Managed Inventory Model for Imperfect Production Process Using Sustainability Investment and Energy Consumption Under Different Carbon Policies

OPTIMAL PRODUCTION POLICY FOR IMPERFECT ITEMS UNDER LEARNING AND FORGETTING ENVIRONMENT

In an imperfect production process with the impact of inflation, this study studies an economic production quantity (EPQ) model with exponential demand. The machine may go from an in-control state to an out-of-control state throughout a lengthy procedure. As a result, the system produces imperfect items. Shortages are permitted and partially backlogged with an exponential rate. We developed the model in both fuzzy and crisp sense. It is well known that as the number of cycle increase the percentage of defective items decrease due to the learning and forgetting effect of the past. Similar in the case of set up cost which also decreases due to the learning and forgetting effect.

A two-tier supply chain model under two distributions with MTTF, rework, variable production rate and lead time

This article considers the two-level supply chain model incorporating an imperfect production process under a variable lead time. The cost of producing a unit item is calculated as a function of the production rate. In addition, two alternative production functions (linear and quadratic functions) are used to relate process quality and production rate. Lead time demand follows two different distributions, based on which two mathematical formulations are described in this paper. In the first model, the lead time demand follows a normal distribution. In the second model, the lead time demand doesn't follow any particular distribution, but the mean and the standard deviation are known. The lead time length is minimized by incorporating the lead time crashing cost. This research aims to analyze the optimized total cost of the supply chain under two different distributions.