Imperfect production inventory model with production rate dependent defective rate and advertisement dependent demand

Manna, Amalesh Kumar; Dey, Jayanta; Mondal, Shyamal Kumar

doi:10.1016/j.cie.2016.11.027

Cited by 109 publications

(37 citation statements)

References 34 publications

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“…Recently, Ref. [17] investigated an unreliable production system with variable demand rate. The study examines defective rate as a function of tha production rate of a system.…”

Section: Manufacturing Unreliabilitymentioning

confidence: 99%

An Automated Smart EPQ-Based Inventory Model for Technology-Dependent Products under Stochastic Failure and Repair Rate

Asghar

Kim

2020

Symmetry

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With the ever-growing technology development, high-tech products such as mobile phones, computers, electromagnetic devices and smart devices are facing high design and production modification requirements with relatively shorter life cycles. For instance, every forthcoming smart phone goes out of production in a shorter period after its launch, followed by its next generation. The design of high-tech products requires high investments in smart and automated manufacturing technology to ensure higher production efficiency. For high-tech products with short life spans, the manufacturing performance-quality variable is an important design parameter that affects system reliability, production efficiency and manufacturing costs. Major performance-quality factors of a manufacturing system which affect productivity and reliability of the manufacturing process are discussed in this research. The study investigates an integrated smart production maintenance model under stochastic manufacturing reliability for technology dependent demand and variable production rate. The smart unit production cost is a function of manufacturing reliability and controllable production rate, as a manufacturing system can be operated at different production rates within designed limits μ ϵ [ μ m i n , μ m a x ] . Manufacturing reliability is increased through investment in smart manufacturing technology and resources. The integrated smart production maintenance model is formulated under general failure and repair time distributions and the optimal production maintenance policy is investigated under specific failure and repair time distributions. A mathematical model is developed to optimize the manufacturing quality-performance parameter, variable production rate, per unit technology investment and production lot size. The total cost function is optimized through the Khun–Tucker method. The mathematical model is also validated with numerical analysis, comparative study, and sensitivity analysis for model key parameters.

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“…Recently, Ref. [17] investigated an unreliable production system with variable demand rate. The study examines defective rate as a function of tha production rate of a system.…”

Section: Manufacturing Unreliabilitymentioning

confidence: 99%

An Automated Smart EPQ-Based Inventory Model for Technology-Dependent Products under Stochastic Failure and Repair Rate

Asghar

Kim

2020

Symmetry

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“…Leung (2009) considered an EMQ model for an imperfect production problem with immediate rework. Some instances of recent studies on imperfect quality items in inventory models are Manna et al (2017a), Manna et al (2017b), Manna et al (2018), De et al (2018) and Manna et al (2019).…”

Section: Introduction and Literature Reviewmentioning

confidence: 99%

Economic lot-size problem for a cleaner manufacturing system with warm-up period

2020

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There are instances that production machines require a warm-up period to reach their anticipated productivity. This study extends an economic manufacturing quantity (EMQ) problem by considering warm-up issue in the model. Warming up the machine decreases production loss, emission, and machine depreciation. Therefore, this study helps industry to enhance the profitability and also to reduce the environmental impact by decreasing waste generation and improving machine efficiency. In this study, we divide our system into three subsystems based on the relationships between production and consumption. Then we provide a mathematical model for each subsystem (three in total). The first two models are single-item EMQ inventory problems and the third one is a multi-item single-machine EMQ problem. In the third model, a machine/facility manufactures some items under a limited manufacturing volume. The purpose of these proposed models is to find the optimum cycle length to minimize the total system cost that consists of manufacturing, inventory and setup costs. Finally, we propose exact solution procedures after proving the convexity of these mathematical models.

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“…(iv) A proportion of items produced are defective/imperfect. This proportion is an increasing function of production rate because the reliability may decrease with increasing production rate (see Manna et al [13]). During production, an automated system will detect and separate the defective items immediately.…”

Section: Assumptionsmentioning

confidence: 99%

“…It happens in many industries due to economies of scale (see Sana et al [12] and Manna et al [13]). Unit cost consists of two cost components: one is fixed cost which incurs due to raw materials, assembling, and so on, and the other component is variable cost which incurs due to energy, labor cost, rent, insurance, and so on.…”

Section: Assumptionsmentioning

confidence: 99%

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Effect of Green Technology Investment on a Production-Inventory System with Carbon Tax

Datta

2017

Advances in Operations Research

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Carbon emissions play the central role in global warming. Manufacturing firms are significant contributors to carbon emissions. In many countries, regulatory authorities are taking actions to reduce emissions. Carbon taxation and cap-and-trade schemes are two mechanisms implemented in many countries. In the present paper, the author analyzes a production-inventory model under a carbon tax system. The production rate is assumed to be a decision variable and can be set at any level within machine limits. A proportion of items produced are defective, and this proportion depends on the production rate. Demand depends on the selling price. Unit price is a decreasing function of the production rate. Emissions can be reduced to some extent by capital investment on green technology, and this capital investment amount is a decision variable. Customers are categorized as retail customers and wholesale customers. A discount is offered to the wholesale customers on the regular selling price. The results are illustrated by a numerical example and a sensitivity analysis is performed.

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Imperfect production inventory model with production rate dependent defective rate and advertisement dependent demand

Cited by 109 publications

References 34 publications

An Automated Smart EPQ-Based Inventory Model for Technology-Dependent Products under Stochastic Failure and Repair Rate

An Automated Smart EPQ-Based Inventory Model for Technology-Dependent Products under Stochastic Failure and Repair Rate

Economic lot-size problem for a cleaner manufacturing system with warm-up period

Effect of Green Technology Investment on a Production-Inventory System with Carbon Tax

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