Managing a sustainable integrated inventory model for imperfect production process with type one and type two errors

Rizky, Novrianty; Wangsa, Ivan Darma; Jauhari, Wakhid Ahmad; Wee, Hui–Ming

doi:10.1007/s10098-021-02194-w

Cited by 8 publications

(2 citation statements)

References 23 publications

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“…Bose and Guha [69] proposed an economic production lot sizing under imperfect quality, on-line inspection, and inspection errors. Unlike previous research, Rizky et al [70] devised an integrated inventory model that considers controllable lead time, defective items, errors in inspection, and variable lead time, all while considering sustainability factors. Taghipour et al [71] conducted a study on the production-inventory-marketing model within a two-stage manufacturer-retailer supply chain.…”

Section: ] Gharaei and Almehdawementioning

confidence: 99%

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

De-la-Cruz-Márquez,

Cárdenas-Barrón,

Porter

et al. 2023

Mathematics

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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.

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Section: ] Gharaei and Almehdawementioning

confidence: 99%

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

De-la-Cruz-Márquez,

Cárdenas-Barrón,

Porter

et al. 2023

Mathematics

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“…Recently, Öztürk et al [24] studied an imperfect production process with random breakdowns, rework, and inspection costs and Khara et al [25] formulated an imperfect production model considering advanced payment and trade credit facilities. Beside these, the works of Malik et al [26], Lin et al [27], and Rizky et al [28] are valuable in this area.…”

Section: Introductionmentioning

confidence: 99%

A Mathematical Model of the Production Inventory Problem for Mixing Liquid Considering Preservation Facility

et al. 2021

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The mixing process of liquid products is a crucial activity in the industry of essential commodities like, medicine, pesticide, detergent, and so on. So, the mathematical study of the mixing problem is very much important to formulate a production inventory model of such type of items. In this work, the concept of the mixing problem is studied in the branch of production inventory. Here, a production model of mixed liquids with price-dependent demand and a stock-dependent production rate is formulated under preservation technology. In the formulation, first of all, the mixing process is presented mathematically with the help of simultaneous differential equations. Then, the mixed liquid produced in the mixing process is taken as a raw material of a manufacturing system. Then, all the cost components and average profit of the system are calculated. Now, the objective is to maximize the corresponding profit maximization problem along with the highly nonlinear objective function. Because of this, the mentioned maximization problem is solved numerically using MATHEMATICA software. In order to justify the validity of the model, two numerical examples are worked out. Finally, to show the impact of inventory parameters on the optimal policy, sensitivity analyses are performed and the obtained results are presented graphically.

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Modelling a sustainable supply chain with variable production and ambiguous carbon emission factor using a genetic algorithm

Karthick

2023

Model. Earth Syst. Environ.

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Managing a sustainable integrated inventory model for imperfect production process with type one and type two errors

Cited by 8 publications

References 23 publications

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

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

A Mathematical Model of the Production Inventory Problem for Mixing Liquid Considering Preservation Facility

Modelling a sustainable supply chain with variable production and ambiguous carbon emission factor using a genetic algorithm

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