A production order quantity model with stochastic demand for a chocolate milk manufacturer

Castro, Edgar; Tabucanon, Mario T.; Nagarur, Nagen

doi:10.1016/s0925-5273(96)00117-x

Cited by 10 publications

(5 citation statements)

References 5 publications

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“…Proses produksi merupakan kegiatan menciptakan atau menambahkan nilai guna suatu barang ataupun jasa [1]. Sehingga perencanaan produksi adalah hal yang sangat penting dilakukan dalam sebuah perusahaan, perencanaan produksi tersebut dilakukan dengan menyeimbangkan biaya produksi dan biaya persediaan [2]. Kelancaran proses produksi merupakan faktor utama yang menunjang perusahaan untuk mencapai tujuan.…”

Section: Pendahuluanunclassified

Model Penentuan Jumlah Produksi yang Optimal pada Rantai Pasok dengan Produsen Tunggal dan Multi-Retailer

Hermawan

Dahda

Andesta

2021

JOPT

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Determining the optimal size of procurement or production is the key word in determining optimal inventory. An integrated procurement and production size optimization model becomes a model that provides optimal results for all parties involved in the supply chain. This study proposes the development of a single producer and multi retailer supply chain model with the aim of minimizing the total inventory cost (TIC). The company distributes products to each retailer for further sale to consumers by the retailer. The annual demand from retailers is assumed to be different. Model development is carried out to obtain optimal production quantities for producers, optimal delivery quantities and determine the optimal number of retailers. The determination is based on the manufacturer's production cycle time is the same as the inventory cycle time at each retailer is the same. A simple algorithm is used to determine the optimal cycle time which can be followed by determining the optimal production size, optimal number of shipments and optimal number of retailers. At the end of this study, a numerical example of the use of a model that has been built based on case study data of a fertilizer industry is presented as a producer and its partners as retailers. The results of the numerical examples that have been carried out show that the optimal number of retailers is 3 retailers with an optimal production of 742 units, the determination of the optimal number of retailers is obtained from experiments with the lowest TIC value.

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Section: Pendahuluanunclassified

Model Penentuan Jumlah Produksi yang Optimal pada Rantai Pasok dengan Produsen Tunggal dan Multi-Retailer

Hermawan

Dahda

Andesta

2021

JOPT

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“…Perencanaan produksi adalah langkah yang sangat penting [1] karena merupakan proses menerjemahkan strategi dan tujuan perusahaan kedalam kegiatan produksi [12], salah satu prosesnya yaitu menentukan berapa ukuran lot produksi perusahaan. Bahan baku merupakan hal paling utama yang harus ada didalam perusahaan, terutama perusahaan industri, karena bahan baku merupakan bagian dari suatu proses produksi yang harus ada didalam perusahaan dan tidak dapat diabaikan keberadaannya, baik dalam kuantitas maupun kualitas yang telah ditentukan oleh perusahaan [8].…”

Section: Pendahuluanunclassified

Model Economic Production Quantity (EPQ) dengan Sinkronisasi Demand Kontinu Dan Demand Diskrit pada Produksi Kerupuk Ikan Sungai Khas Kalimantan Timur

Fibriani

Cahyadi

2018

j. St. terap

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Model Economic Production Quality (EPQ) mengarahkan perusahaan agar dapat meminimalkan total biaya produksi dengan mereduksi biaya inventori. Parameter model dasar EPQ adalah demand, biaya setup mesin dan biaya simpan persediaan. Namun dalam kenyataanya perusahaan tidak hanya memiliki demand yang bersifat kontinu, namun sering kali terjadi demand diskrit yang pemenuhannya dilakukan dalam suatu rentang waktu tertentu. Begitu pula halnya dengan UD. Sanda sebagai produsen kerupuk ikan khas Kalimantan Timur, dalam pemenuhan kebutuhan konsumen terdiri dari 2 tipe demand. Penelitian ini menggunakan metode kuantitatif. Dari peninjauan jumlah permintaan dan perhitungan terhadap tingkat persediaan, diperoleh waktu siklus pengiriman optimal adalah 2 kali dan biaya rata-rata satu periode adalah Rp. 3.336.750,- serta biaya total sebesar Rp. 6.673.500

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“…Demand uncertainty is prevalent in many industries and its importance is beyond doubt (e.g., dos Santos & Kleinkauf, 1999; Law & Au, 1999; Carey, 1998; de Castro, Tabucanon, & Nagarur, 1997). Although the rapid development of computer technologies enables companies to increase the amount of knowledge about their customers, the parameters describing demand remain hard to estimate (Bok, Lee, & Park, 1998).…”

Section: Terminology and Literature Reviewmentioning

confidence: 99%

Coordinating Service‐Sensitive Demand and Capacity by Adaptive Decision Making: An Application of Case‐Based Decision Theory*

2005

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The subject of this article is the simultaneous choice of product price and manufacturing capacity if demand is stochastic and service-level sensitive. In this setting, capacity as well as price have an impact on demand because several aspects of service level depend on capacity. For example, delivery time will be reduced if capacity is increased given a constant demand rate. We illustrate the relationship between service level, capacity, and demand reaction by a stylized application problem from the after-sales services industry. The reaction of customers to variations in service level and price is represented by a kinked price-demand-rate function. We first derive the optimal price-capacity combination for the resulting decision problem under full information. Subsequently, we focus on a decision maker (DM) who lacks complete knowledge of the demand function. Hence the DM is unable to anticipate the service level and consequently cannot identify the optimal solution. However, the DM will acquire additional information during the sales process and use it in subsequent revisions of the price-capacity decision. Thus, this decision making is adaptive and based on experience. In contrast to the literature, which assumes certain repetitive procedures somewhat ad hoc, we develop an adaptive decision process based on case-based decision theory (CBDT) for the price-capacity problem. Finally, we show that a CBDT DM in our setting eventually finds the optimal solution, if the DM sets the price based on absorption costs and adequately adjusts the capacity with respect to the observed demand.

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A production order quantity model with stochastic demand for a chocolate milk manufacturer

Cited by 10 publications

References 5 publications

Model Penentuan Jumlah Produksi yang Optimal pada Rantai Pasok dengan Produsen Tunggal dan Multi-Retailer

Model Penentuan Jumlah Produksi yang Optimal pada Rantai Pasok dengan Produsen Tunggal dan Multi-Retailer

Model Economic Production Quantity (EPQ) dengan Sinkronisasi Demand Kontinu Dan Demand Diskrit pada Produksi Kerupuk Ikan Sungai Khas Kalimantan Timur

Coordinating Service‐Sensitive Demand and Capacity by Adaptive Decision Making: An Application of Case‐Based Decision Theory*

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