Designing supply chain analysis tool using SCOR model (Case study in palm oil refinery)

Lestari, Fitra; Ismail, Kamariah; Hamid, Mohd. Kamaruddin Abd.; Sutopo, Wahyudi

doi:10.1109/ieem.2013.6962546

Cited by 6 publications

(4 citation statements)

References 8 publications

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“…Penelitian yang membahas penerapan pengukuran kinerja model SCOR cukup banyak dilakukan pada industri manufaktur, antara lain (Hasibuan & Dzikrillah, 2018) di industri kimia, (Sellitto et al, 2015;Wahyuniardi et al, 2017) di industri alas kaki, (Liputra et al, 2018) di industri kemasan Produk, (Lestari et al, 2013) di industri minyak sawit, (Seifbarghy et al, 2010) di industri logam, (Pothasst et al, 2010) di industri automotive, (Ambe, 2014) di industri kendaraan ringan (Cheng et al, 2010) di industri konstruksi, (Schnetzler et al, 2009) di industri kayu, (Vanany et al, 2005) di industri lampu, (Sri Hartini et al, 2019) di industri garam dan (Fauziyah et al, 2020) di industri makanan halal. Penelitian terdahulu yang menggunakan metode kombinasi SCOR dan AHP untuk mengukur kinerja rantai pasok perusahaan antara lain Mendoza (2014) dan Anwar (2108) untuk menentukan metrik SCOR yang terpenting adalah mengidentifikasi metrik yang relevan untuk dilakukan perbaikan, Ponis et al, (2015) menggunakan metode SCOR dan AHP untuk membangun model framework penilaian kinerja rantai pasok, pada penelitiannya AHP dan pembobotan digunakan sebagai pemilihan kriteria yang memungkinkan untuk framework penilaian rantai pasok perusahaan, Sri Hartini., et al (2019) menggunakan metode SCOR dan AHP untuk menentukan KPI sebagai alat pengukuran kinerja rantai pasok industri garam.…”

Section: Supply Chain Operation Reference (Scor)unclassified

Framework pengukuran kinerja rantai pasok industri kemasan plastik menggunakan metode SCOR-AHP

Aryanto

Hasibuan

2021

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The manufacturing industry in general cannot be separated from the role of the plastic industry. In Indonesia, there are 925 companies that produce various kinds of plastic products for the food and beverage industry, automotive industry, pharmaceutical industry and other industries. Companies are faced with challenges to improve their supply chain competitiveness, while plastic packaging companies generally do not have a comprehensive performance measurement framework in their supply chains. The purpose of this research is to select and determine the level of importance of the Key Performance Indicator (KPI) for measuring the supply chain performance of the plastic packaging industry using the SCOR and AHP framework. In the initial stage, 45 KPIs were identified, from the results of expert validation, 29 KPIs were distributed to the dimensions of reliability, responsiveness, flexibility, cost, and assets. At the level 1 hierarchy the greatest level of importance is generated in the dimensions of reliability (A1), asset management (E1), responsiveness (B1), cost (D1), and flexibility (C1) with weights of 0.262, 0.209, respectively. 0.191, 0.175, and 0.163. The largest distribution of KPIs is on the reliability dimension, namely 32%, followed by the cost dimension of 16%, 12% responsiveness, flexibility and asset management have the same distribution, namely 4%. Based on the results of weighting using the AHP method, a supply chain performance measurement framework is recommended in the case of the plastic packaging industry.

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Section: Supply Chain Operation Reference (Scor)unclassified

Framework pengukuran kinerja rantai pasok industri kemasan plastik menggunakan metode SCOR-AHP

Aryanto

Hasibuan

2021

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“…Obviously, the activity of blood distribution from donors to patients in form a flow of product which it can be studied based on supply chain strategy. Lestari et al [2] revealed that the supply chain strategy is the integration of activities including several entities to provide the best service to the end consumer.…”

Section: Introductionmentioning

confidence: 99%

Managing Inventory on Blood Supply Chain

Lestari

Ulfah²,

Nugraha

et al. 2018

Transactions on Engineering Technologies

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There is unbalance the amount of blood demand and the availability of blood for each component at Blood Transfusion Unit in Indonesia. As the result, this component run into inventory shortage so management need to maintain the strategy of blood supply chain for the patients. Purpose of this is to manage inventory on the blood component of Packed Red Cells which it to be the highest blood component requirement for patient in this case study. Managing inventory is done through several stages including forecasting method, safety stock, and reorder point. Finding of this study was obtained that exponential smoothing (α 0.95) to be the best forecasting method. Then, to manage inventory, this agency need to prepared 34 blood bags for safety stock and 76 blood bags for reorder point. This results able to give recommendation to the Blood Transfusion Unit at Indonesia regarding with the number of blood component provided and how much reorder to be made at the time of reaching the lead time. Further study is suggested to conduct simulation method in order to evaluate policy in managing blood inventory and prepare scenario for optimizing inventory level.

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“…This study is conducted using the Supply Chain Operation Reference (SCOR) model to identifies the process based on Supply Chain activities such as Plan, Source, Make, Deliver and Return. SCOR model has been done to designing supply chain analysis tool [16], Evaluation of valuable chain in palm oil company [17], Measuring the value added of oil palm products and discrete event simulation [18] and supply chain configuration [19].…”

Section: Introductionmentioning

confidence: 99%