Purchasing Management: The Optimisation of Product Variance

Uhl, Christian; Nabhani, Farhad; Kauf, Florian; Shokri, Alireza; Hughes, David

doi:10.1016/j.promfg.2017.07.266

Cited by 5 publications

(4 citation statements)

References 25 publications

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“…Kebutuhan busi sebagai komponen pengganti pada kendaraan mempunyai permintaan yang cukup besar, khususnya bagi manufaktur busi asal Jepang yang telah berdiri sejak 40 tahun yang lalu di Indonesia. Perusahaan melakukan penjualan untuk mensuplai komponen kepada manufaktur produsen kendaraan (Principle) atau yang biasa disebut OEM (Original Equipment Manufacturer) yaitu penjualan yang diperuntukkan sebagai barang setengah jadi dari produk kendaraan oleh Principle (Uhl et al, 2017) (Gaikindo, 2018). Pada penjualan aftermarket (AM) menjadi bagian penjualan terpenting.…”

Section: Pendahuluanunclassified

Integrasi forecasting pada rantai pasok manufaktur komponen otomotif Jepang di Indonesia dengan penerapan metode classic dan regresi

Patria

Sudarto

2020

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The need of spark plugs as a replacement component has a potential demand, especially for a Company from Japan which establish in the last 40 year ago as manufacture of spark plugs in Indonesia. Sales forecast of spark plugs that develop by Company for aftermarket class has big error. It makes a question ‘how to improve the accuracy of forecasting spark plugs in the aftermarket class to reduce losses in the supply chain process’, such as loss due to inventory, production and transportation. In this study, it was found that using ARIMA and MLR methods could increase level of accuracy than current forecasting method by Company. It was found that the increment in forecasting accuracy by using ARIMA and MLR was able to reduce operational costs up to 25.05% per year in overtime costs and 40.21% per year in finished goods inventory costs. In addition, reducing the cost of shipping materials by 24.90% per year, and reducing inventory costs on suppliers by 25.74% per year.

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Section: Pendahuluanunclassified

Integrasi forecasting pada rantai pasok manufaktur komponen otomotif Jepang di Indonesia dengan penerapan metode classic dan regresi

Patria

Sudarto

2020

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“…Fast and effective product development is a need and must include two parameters: product quality improvement and reduction of production costs. In the papers (Liu et al, 2016;Meng et al, 2017;Uhl et al, 2017), different optimization problems are presented according to the product lifecycle stage. In Liu et al (2016), the problem of product design optimization via associative optimization feature modeling is analyzed.…”

Section: Introductionmentioning

confidence: 99%

“…Another product optimization problem could be related with the production process and supply chain management. Product optimization due to these problems is described in Uhl et al (2017). The use of the design of experiments (DOE) methodology allows to evaluate the various parameters impact on the final result.…”

Section: Introductionmentioning

confidence: 99%

Numerical optimization methods comparison based on the CFD conduction-convection heat transfer case

Młynarczyk

2019

HFF

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Purpose In some types of industries, the best possible design, in terms of thermal and flow performance, determines the success or failure of the company. This applies, among others, to the sectional elements that form doors, windows or prefabricated building walls. The purpose of this paper is to show the possibilities and limitations of the different response surface methods for optimization in the case where natural convection phenomenon appears inside the sectional structures. Design/methodology/approach A three-layered wall with air gap is used as a cross-section heat flow model. Response surface algorithms for optimization, which can be found in commercial software, e.g. ANSYS/WORKBENCH, can help to optimize geometrical structure of components to achieve bigger or smaller heat flux value. In this paper, the optimization methodology of the design of experiments (DOE) and different response surface (RS) methods are used. Findings Optimal results obtained with the use of genetic aggregation, standard RS, Kriging, non-parametric regression and neural network methods are compared with direct CFD and analytical calculations. Different limitations and advantages of the RS methods make individual methods more appropriate for different issues. For a properly defined optimization problem, the heat flux value approximated for the optimal geometry agrees with the direct CFD simulations. Practical implications The presented investigations show how to use response surface optimization methods for thermal optimization of the sectional elements and their applications to obtain reliable results. Originality/value This paper presents the value of the use of RS methods in CFD-based geometry optimization. The study also shows that the RS optimization methods can approximate thermal properties under natural convection development conditions.

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“…Companies must choose the most appropriate supplier, because the selection of sup-pliers significantly reduces raw material costs and increases company competitive-ness, but inaccurate supplier selection can cause financial and operating problems. On the other hand, supplier selection can make the company more efficient and can produce higher quality products [1]. For this reason, the company tries to determine the supplier of the company where there are 4 criteria considered by the company.…”

Section: Introductionmentioning

confidence: 99%

Determination of Supplier and Order Quantity of Raw Material Using Ahp Method and Linear Programming

Alfaris

Qurtubi

2019

JMMST

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Companies must choose suppliers properly, because the selection of the right supplier can reduce raw material costs and increase the competitiveness of the company, while improper supplier selection can cause financial and operating problems. The purpose of this study is to determine the optimal supplier and order quantity of raw materials. As for the object of the research is a multipurpose technology machinery company. Data collection methods used in this study were observation, interviews, and questionnaires. Supplier data is processed using the AHP method to determine the right supplier, while the linear programming method is used to determine the order quantity of the raw material. Based on the calculation, the DS supplier gets a weight of 0.65 and the LG supplier gets a weight of 0.35. The optimal order quantity from each supplier is 7.5 tons for DS and 7.5 tons suppliers for LG suppliers. From the results of the optimization, the cost reduction figure is Rp. 3,750,000 or 3% of the total cost of purchase.

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Purchasing Management: The Optimisation of Product Variance

Cited by 5 publications

References 25 publications

Integrasi forecasting pada rantai pasok manufaktur komponen otomotif Jepang di Indonesia dengan penerapan metode classic dan regresi

Integrasi forecasting pada rantai pasok manufaktur komponen otomotif Jepang di Indonesia dengan penerapan metode classic dan regresi

Numerical optimization methods comparison based on the CFD conduction-convection heat transfer case

Determination of Supplier and Order Quantity of Raw Material Using Ahp Method and Linear Programming

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