Production Run Time Research Articles

The effects of inflation, shortages, and partial backlogs on products that deteriorate over time in response to varied demand

This study aims to determine an optimal policy to deal with a situation where a retailer should have enough stock to meet customer demands and prevent supply loss and deterioration. In this study, we demonstrate the impact of partial backlogging, shortages, and inflation on decaying items to provide the most relevant solutions to this problem. The model uses a two-parameter Weibull deterioration distribution with an exponential demand rate. Numerical results and sensitivity analysis are combined with a graphical demonstration, and the proposed approach is reliable and accurate, providing a new explanation for a different type of system. This paper determines the total cost and optimal production run time by developing an inventory model. Sensitivity analysis is carried out to demonstrate the proposed model.

A Novel Model for Economic Recycle Quantity with Two-Level Piecewise Constant Demand and Shortages

This paper focuses on the production systems that may produce a proportion of recyclable defective products. The developed model is called an Economic Recycle Quantity (ERQ) model with the assumption of a full recovery of defective items. The defective parts are collected during the production-off time and can be used during the next production cycle of the same category. The demand rate of the non-defective items is a two-level piecewise factor—one during the production-run time and another during the production-off time. The developed model aims to optimize the total inventory cost, the order quantity, and the amount of recyclable defective items that represent the ERQ. The mathematical formulations of the model are deduced theoretically. The model was solved analytically, and the optimal results are illustrated. Sensitivity analysis is carried out to investigate the effect of varying system parameters and validate the proposed model. Results of the sensitivity analysis show that the consideration of defective part recycling reduces the total inventory cost where the raw material is reduced. The cost reduction is about 1%; of course, the environmental impact is more appreciated. Furthermore, the managerial implications are described, and the future perspectives are discussed.

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 Circular Economy and Process Maintenance Strategies for an Imperfect Production–Inventory Model with Scrap Returns

To protect our environment, current firms are committed to the circular economy and process maintenance strategies to reduce the waste of resources. In this way, they can also save costs and create an enterprise image and value. Therefore, this study explores an imperfect production system with a circular economy and process maintenance activities, wherein the defective products can be converted into scrap returns (i.e., secondary raw materials) and products can be manufactured using mixed materials containing scrap returns. The proposed system considers multiple products with varying feed rates of scrap returns. According to the scenario of the aforementioned production system, this paper develops a production–inventory model aimed at cost minimization, in which the production run time, purchased quantity of material, number of maintenance times, and recovery rate are decision variables. Furthermore, we also develop a computational algorithm to obtain these optimal solutions efficiently. Finally, the numerical and sensitivity analyses based on a practical case are presented to illustrate the applicability of our method and some managerial implications. For example, both strategies efficiently reduce the total cost per unit time in the proposed numerical example. The sensitivity results can be used to determine the optimal combination of two strategies and the execution moment under various changes in cost parameters.

A Brief Review on The Common Defects in Wire Arc Additive Manufacturing

Wire arc additive manufacturing (WAAM) process, which depends on conventional welding arc processes, is a promising option for industries when compared to typical manufacturing processes for assembling large and complicated products. WAAM process attracting manufacturing industries due to its potential to make large and complicated components with real sharp production run time with almost single step process. The process represents greater material savings, higher material buildup rate and speed, cost savings, lower cycle time, less impact on the environment, and capability of producing large size parts when evaluated with other fabrication methods. This paper focuses on WAAM process and reviews some of the common possible process defects found in variety of studies made previously to summaries a guideline for the causes of such defects and provides some prevention methods found by those studies. Of these common possible defects found in researchers works and reviewed in this work are pores, lack of fusion, cracks, and residual stress.

Optimum buffer stock during preventive maintenance in an imperfect production system

The paper investigates a production‐inventory model where regular preventive maintenance starts at the end of production for smooth functioning in the next cycle. During production run time, the manufacturing system may shift from “in‐control” state to “out‐of‐control” state after a certain time. The manufacturing system produces imperfect quality products during “in‐control” state and “out‐of‐control” state with different rates, and these imperfect quality products are reworked at costs in parallel system. The whole items are sold with free minimal repair warranty if any fault arises after sale. This study extends and corrects the Sana's production‐inventory model and derives optimal buffer inventory to minimize the expected costs per unit item. A numerical illustration with its sensitivity analysis of the key parameters is studied to justify the proposed model.

Destabilization of Aβ fibrils by omega-3 polyunsaturated fatty acids: a molecular dynamics study

The senile plaques of neurotoxic aggregates of Aβ protein, deposited extraneuronally, mark the pathological hallmark of Alzheimer’s disease (AD). The natural compounds such as omega-3 (ω-3) polyunsaturated fatty acids (PUFAs), which can access blood–brain barrier, are believed to be potential disruptors of preformed Aβ fibrils to cure AD with unknown mechanism. Herein, we present the destabilization potential of three ω-3 PUFAs, viz. Eicosapentaenoic acid (EPA), Docosahexaenoic acid (HXA), and α-linolenic acid (LNL) by molecular dynamics simulation. After an initial testing of 300 ns, EPA and HXA have been considered further for extended production run time, 500 ns. The increased value of root mean square deviation (RMSD), radius of gyration, and solvent-accessible surface area (SASA), the reduced number of H-bonds and β-sheet content, and disruption of salt bridges and hydrophobic contacts establish the binding of these ligands to Aβ fibril leading to destabilization. The polar head was found to interact with positively charged lysine (K28) residue in the fibril. However, the hydrophobicity of the long aliphatic tail competes with the intrinsic hydrophobic interactions of Aβ fibril. This amphiphilic nature of EPA and HXA led to the breaking of inherent hydrophobic contacts and formation of new bonds between the tail of PUFA and hydrophobic residues of Aβ fibril, leading to the destabilization of fibril. The Molecular Mechanics Poisson–Boltzmann Surface Area (MM-PBSA) results explain the binding of EPA and HXA to Aβ fibril by interacting with different residues. The destabilization potential of EPA and HXA establishes them as promising drug leads to cure AD, and encourages prospecting of other fatty acids for therapeutic intervention in AD. Communicated by Ramaswamy H. Sarma

An Imperfect Production–Inventory Model with Mixed Materials Containing Scrap Returns Based on a Circular Economy

The implementation of scrap recovery activities has been shown to improve the financial performance of many firms, and this kind of circular economy (CE) is particularly evident in industries with green manufacturing (GM). In this paper, we consider an imperfect multiple-stage production system that manufactures paired products made from mixed materials containing scrap returns, in which the scrap returns are converted from defective products. The feed rates of scrap returns for two products are different, and the product with the higher feed rate is placed in the second order of the process to avoid unlimited accumulation of scrap returns. The proposed problem is formulated as a joint economic order quantity (EOQ) and economic production quantity (EPQ) model aimed at cost minimization. The decision variables of the proposed model include the production run time of two products, order quantity of new material, and the extent of investment in converted equipment. We also prove that the optimal solution exists uniquely and provide an algorithm for the computation of the optimal solution. Finally, a numerical example involving the pulp and paper manufacturing industry is provided to illustrate the solution process, and the results of its sensitivity analysis are also presented to show some managerial implications.

Adjustment of credit period and stock-dependent demands in a supply chain model with variable imperfectness

In this model, a supply chain model has been developed where a manufacturer continuously transports perfect quality items at no cost to a distribution center to maintain the market demand. At the beginning of the process, the production process is in an “in-control” state, but after a random time, it goes to an “out-of-control” state. Thus the production process produces perfect as well as imperfect items in this state. The rate of imperfect production depends on production rate and production-run length in the “out-of-control” state. The unit production cost of the manufacturer depends on the production rate which indicates that the higher production rate is the cause of higher production cost if it exceeds the normal production rate set by the manufacturer. The manufacturer provides a credit period to the distributor to increase his sales growth. In the competitive business world, credit period affects the demand rate of a retailer/buyer due to its late payment facility. So, here, credit period dependent demand function is introduced for the distributor. During the festive season, demand factor of products is usually affected by stock level. Also, for some types of products (such as clothing), the demand factor depends on its stock level. Thus we have considered stock-dependent demand function for the customers. Now, in an infinite time horizon, the problem is how they adjust their demands to sustain the whole system’s financial flow. The novelty of this model is to analyze the compatibility of this two-type of demand in their businesses so that both can maintain their profits. Also, there is another credit length which is offered by the distributor. The proposed model has been discussed in type-2 fuzzy environment due to the uncertainty of the credit period. The purpose of this model is to optimize the integrated profit of the system by optimizing production rate and production-run time. Finally, numerical examples have been provided to illustrate the feasibility of both crisp and fuzzy model and some conclusions are derived conducting a sensitivity analysis of different parameters.

Effects of corporate social responsibility activities in a two-stage assembly production system with multiple components and imperfect processes

Implementation of corporate social responsibility (CSR) activities has been shown to improve the financial performance of many firms, and the effects are particularly evident in original brand manufacturers (OBMs). This paper studies the effects of two common CSR activities (social donations and green industrial development) on a two-stage assembly production system with multiple components and imperfect processes under the assumption that demand depends on selling price and CSR impact. The proposed problem is formulated as an economic production quantity (EPQ) model aimed at profit maximization, in which the decision variables include the production run time of each process, expenditures on social donations, and green industrial development. Our results prove that an optimal solution exists, and that it is unique. An algorithm for the computation of the optimal solution is also provided. The efficacy of the proposed model is demonstrated via numerical modeling of a footwear OBM in Taiwan. Sensitivity analysis revealed a number of managerial insights. For example, the results obtained under CSR operations can be compared with those obtained under non-CSR operations (under various parameters settings) to determine an opportune moment for the execution of CSR.

Autonomated Inspection Policy for Smart Factory—An Improved Approach

The proposed model focuses on an imperfect production process (IPP) in which, during long-term production, the system may change to an “out-of-control” state from an “in-control” state and produce some imperfect products because of a long production run length. Brand image and industry reputation are affected by product defectiveness. To increase the profit of any industry and improve reputation and brand image, inspection of the production system is required. However, this inspection is subjected to human error, which negatively affects the assessment of production systems. Herein, an error-free inspection is performed with the help of an autonomation policy, in which each product is inspected via a machine instead of a human, facilitating an error-free inspection and converting the production system to a smart production system. Moreover, in reality, product demand cannot always be constant. Therefore, in this model, a selling-price-dependent demand is considered along with a variable production rate to enhance model applicability. Moreover, total system profit is optimized and optimal values for production run time, inspection scheduling, selling price, buffer inventory, and production rate are determined. Finally, for model validation, some numerical examples along with special cases are provided. The concavity of the optimal function is also proven through graphical illustration. The sensitivity of the key parameters of the presented model is explored and the significance is explained.

Imperfect Production Inventory Model with Uncertain Elapsed Time

Most of the classical inventory control model assumes that all items received conform to quality characteristics. However, in practice, items may be damaged due to production conditions, transportation and environmental conditions. Modelling such real world problems involve various indeterminate phenomena which can be estimated through human beliefs. The uncertainty theory proposed by Liu (2015) is extensively regarded as an appropriate tool to deal with such uncertainty. This paper investigates the optimum production run time and optimum cost in an imperfect production process, where the rate of imperfect items are different in different states of the process. The process may be shifting from ‘in-control’ state to the ‘out-of-control’ state is an uncertain variable with certain uncertainty distribution. Some propositions are derived for the optimal production run time and optimized the expected total cost function per unit time. Finally, numerical examples have been illustrated to study the practical feasibility of the model.

Lead-time Dependent Ordering Cost Reduction and Trade-credit: A Supply Chain Model with Stochastic Demand and Rework

This study focuses on an integrated vendor-buyer supply chain model where the lead-time and ordering cost reduction act dependently. The lead time demand of a product follows a normal distribution. The manufacturing process is imperfect. During production run time, a certain percentage of defective products are produced, which are immediately reworked. Trade-credit financing has been taken into consideration. The goal of this study is to minimize the joint total expected cost by providing an inter-dependent reduction strategy of lead-time and ordering cost along with the determination of the optimal values of lead-time, number of deliveries, order lot size, ordering cost, lead-time crashing cost, and the joint total expected cost. A solution algorithm and a numerical example are presented to illustrate and establish the integrated model. This model can be used in textiles, automobiles and computers industries.

Investment for process quality improvement and setup cost reduction in an imperfect production process with warranty policy and shortages

Cost reduction for setup and improvement of processes quality are the main target of this research along with free minimal repair warranty for an imperfect production System. This paper deals with the effect of setup cost reduction and process quality improvement on the optimal production cycle time for an imperfect production process with free product minimal repair warranty. Here the production system is subject to a random breakdown from ancontrolledsystem to anout-of-controlstate. Shortages are fully backlogged. The main target to minimize the total cost by simultaneously optimizing the production run time, setup cost, and process quality. A solution algorithm with some numerical experiments are provided such as the proposed model can illustrate briefly. Sensitivity analysis section is decorated for the optimal solution of the model with respect to major cost parameters of the system are carried out, and the implications of the analysis are discussed.

A hybrid carbon policy inventory model with emission source-based green investments

The present study analyzes a production-inventory system with hybrid carbon regulation policy. This hybrid carbon policy is a combination of carbon tax and cap-and-trade policies. It considers a single item that can be produced in different qualities. Production cost, setup cost, amount of emissions and the demand rate depend on the quality. The demand rate for each quality is price sensitive. Emissions occur from three sources—setup, production process and stock holding. The firm can invest on green technologies in each emission source separately to reduce emissions. This model considers profit maximization policy. The managerial problem is to select the profit-maximizing quality for production, and to find the optimum values of the production run time, green investments and the selling price. An algorithm is provided to solve the model. The model is illustrated by a numerical example. Sensitivity analysis is also performed.

Optimizing profit for pricing and advertisement sensitive demand under unreliable production system

ABSTRACT This article deals with an imperfect economic production quantity (EPQ) model with an unreliable production system where the customers' demand depends on both selling price and advertisement. During the long run production process the machinery system goes into ‘out-of-control’ state after a random time τ and after that the system produces both perfect and imperfect quality items together. The imperfect or defective quality items are reworked to get it back as the perfect ones at a cost just after the regular production run time. The production process of imperfect quality items depends on the reliability of the machinery system where the failure rate may be variable. Here, we consider that the random time variable τ follows the two parameters ‘Weibull distribution’. The objective of this article is to maximize the expected average profit function of the unreliable system with respect to ordering lot size, selling price and frequency of advertisement. We use the incomplete gamma function to formulate the expected average profit function. The model is validated by numerical examples and sensitivity analysis is provided to illustrate the model.

Manufacturer's pricing and lot-sizing decisions for perishable goods under various payment terms by a discounted cash flow analysis

In practice, a cash payment is a classical payment term, a credit payment is commonly applied to stimulate sales, and an advance payment is used to avoid order cancellations. A combination of these three payment types is considered an advance-cash-credit (ACC) payment scheme, which is commonly used in business transactions. For instance, a home buyer must pay a homeowner 1% of the listing price as a good-faith deposit (i.e., an advance payment) to start negotiating the price, then pay 10% of the agreed-upon price (i.e., a cash payment) when signing the contract, and then has a delay before the final payment (i.e., a credit payment, a mortgage) is approved. In this paper, we develop an economic production quantity (EPQ) model for perishable goods in a three-echelon supplier-manufacturer-customer chain: (1) demand rate depends on selling price and freshness of a perishable item (i.e., time to sell-by date), and (2) the supplier offers an upstream ACC payment to the manufacturer, while the manufacturer grants a downstream cash-credit payment to customers. Consequently, the manufacturer must determine optimal selling price, production run time, and replenishment cycle time to maximize the present value of total annual profit by using a discounted cash flow (DCF) analysis. The proposed model fits in a general framework that includes numerous previous models as special cases. The numerical results reveal that the present value of total profit is joint concave in both selling price and cycle time. Finally, a sensitivity analysis is performed and managerial insights are also provided.

A Single Period Production Inventory Model in Interval Environment with Price Revision

In the present competitive market, in case of some products like smartphone, it is observed that after few days of launching a new product, a same type of product by some other company becomes available with a cheaper selling price or with more accessories within the same selling price. In this situation, customers normally go for the new product rejecting the older one. So always there is a possibility that some units of product remain unsold. This compels the company for a revision in selling price. This paper aims to develop such kind of production inventory models. Here demand of the product depends upon the selling price of the product, promotional effort and time. Now-a-days, specially for those kind of products, demand mainly depends on these three parameters in real life situation. When demand becomes zero, company sets a new selling price and the remaining products are depleted at a constant demand. So obviously it is going to be a single period inventory model. As a real life production process can not be hundred percent perfect, during the production process, some defective items are also produced which are reworked after the regular production process. Also, in order to reflect practical situation, inventory cost parameters are taken as interval numbers. As a result the corresponding optimization problem becomes interval valued which has been solved by using quantum-behaved particle swarm optimization technique. The main objective of this paper is to determine the optimal production run time that maximizes the total profit of the company.

Optimal production run time for an imperfect production inventory system with rework, random breakdowns and inspection costs

In real-life manufacturing systems, the presence of defective products in a lot is inevitable. While these products may be just scrapped in the food industry, in high-tech industries where the final product is very expensive, they may be reworked at a cost. A common assumption in the literature is that the inspection time needed to identify defective items is completed when the production process ends. However, the assumption of continuous inspection during production complicates the analysis, making it impractical for most production systems, especially when the production rate is high, and the proportion of defective items is low, making continuous inspection during production very expensive. In addition, such factors as process deterioration or other uncontrollable factors in the production process may interrupt the production of the lot. To address these practical issues, this paper integrates inspection time and the failure of production facilities into an imperfect production inventory model with rework, where the production run time is a decision variable and an inspection process continues even after a production run; the paper demonstrates significant effects on the optimal solutions, with shortages not allowed. Under these assumptions, a mathematical model is derived, and the concavity of the expected total profit function is proved. Optimal policy is obtained by applying the analytic method. Special cases of the model are studied and a numerical example with sensitivity analysis is provided to draw insights. Moreover, this numerical example is used to compare general and special cases.

Determining an optimal replenishment run time and lot size for an imperfect manufacturing system and rework under markdown policy

This study proposes a continuous production inventory model for deteriorating items with preservation technology, rework and price-dependent demand under markdown policy. In this study, we have adopted the markdown policy to reduce inventory cost and clearance at the end of the season or to sell old or slow-moving inventory at the end of its life. Rework is another main factor to reduce production cost and environmental problem. The preservation technology is also considered during product deterioration period to control the deterioration rate of products. The shortages are not allowed. We have also considered that in one cycle, the production system can produce items in several determined replenishment cycles under markdown policy. The aim of this research is to derive the optimal production-run time, the optimal replenishment cycle length, the optimal length of time horizon and the optimal production quantity so as to minimize the total average cost. An example and sensitivity analysis is shown to illustrate the model.