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"This book provides an insight of relevant case studies and updated practices in “PharmaceuticalSupply Chains” (PharmSC) while addressing the most relevant topics within the COST Action “Medicines Shortages” (CA15105).The volume focuses on the most recent developments in the design, planning and scheduling ofPharmSC, broadening from the suppliers’ selection to the impact on patients and healthcaresystems, addressing uncertainty and risk mitigation, and computational issues. It is directed at MSc/PhD students and young researchers (Post-Docs) in Pharmaceutics/Pharmaceutical sciences, Engineering fields, Economics/Management, as well as pharmaceutical decision makers, managers, and practitioners, and advanced readers demanding a fresh approach to decision making for PharmSC. The contributed chapters are associated with the homonymous COST Training Schools (TS), and the book creates a better understanding of the Action “Medicines Shortages” challenges and opportunities."

"Penelitian ini bertujuan untuk memperoleh matriks pengukuran kinerja pada perusahaan berbasis produksi obat-obatan. Penilaian kinerja ini bisa digunakan untuk membantu perusahaan untuk mengidentifikasi kondisi saat ini dari supply chain, mencari akar masalah dan melakukan perbaikan pada kinerja rantai pasok. Matriks-matriks supply chain yang digunakan adalah berasal dari supply chain operation reference (SCOR) model. Setiap matriks akan dilakukan peninjauan pertama apakah matriks ini penting digunakan pada industri farmasi.Setelah dilakukan verifikasi dan pemilihan matriks yang akan digunakan, langkah selanjutnya adalah melakukan penilaian dengan membandingkan secara berpasangan matriks kinerja (Pairwise Comparison Matrix) dengan metode AHP. Hasil pembobotan tersebut digunakan untuk menentukan peringkat matriks kinerja dengan menggunakan metode TOPSIS. Matriks yang terpilih dinilai sebagai kriteria matriks yang paling penting dan dijadikan bahan untuk mendapatkan solusi terbaik untuk mencapai performa maksimum perusahaan.

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The objective of this research is to obtain performance measurement matrices of a pharmaceutical company. This performance scoring can be used to help the company to identify the current condition of the supply chain, to find the root cause of the problem, and to improve supply chain performance. Supply chain matrices used are derived from the supply chain operation reference (SCOR) model. Each matrix will be reviewed whether this matrix is important to be used in pharmaceutical industry.

After the verification and selection of the matrices, next step is scoring by doing pairwise comparison of the performance matrices with AHP method. The result then used to determine the rank of performance matrices using TOPSIS method. The highest ranked matrix then selected as the most important matrix and can be used as a source to get the best solutions to achieve maximum performance of the company."

"Peramalan merupakan salah satu hal yang dibutuhkan untuk mencapai tingkat manajemen rantai pasok yang baik. Peramalan dapat mencegah kelebihan pembelian dan juga menjaga ketersediaan barang dengan baik. Peramalan dapat menjadi salah satu metode untuk melakukan menjaga ketersediaan obat di rumah sakit. Obat sendiri merupakan salah satu barang yang sensitif dan reaktif, hal ini menyebabkan obat harus memiliki penyimpanan khusus dan tidak bisa disimpan dalam waktu lama. Dilain pihak, pada industri rumah sakit, ketersediaan obat harus selalu ada. Hal tersebut membuat rumah sakit harus memiliki peramalan obat yang akurat untuk menjaga ketersediaan obat dan mengurangi kelebihan pembelian dan penyimpanan obat dalam waktu lama. Penelitian kali ini akan membandingkan metode tiga metode peramalan, yaitu single exponential smoothing, autoregressive integrated moving average (ARIMA), dan artificial neural network (ANN). Penelitian ini bertujuan untuk melihat dan menganalisa metode peramalan yang paling baik dari ketiga metode yang ada. Penelitian kali ini akan mengambil data penjualan sebanyak 62 periode dari 3 jenis obat dengan kategori obat fast-moving, yaitu Rhinofed, Simvastatin, dan Betahistin. Berdasarkan hasil penelitian, peramalan dengan metode artificial neural network (ANN) memiliki nilai error yang kecil, sehingga nilai ketepatannya cukup besar. Jika dibandingkan dengan kedua metode lainnya peramalan dengan menggunakan metode artificial neural network masih memiliki nilai error yang paling kecil sehingga nilai ketepatan peramalannya yang paling besar. Hal tersebut menyimpulkan bahwa peramalan dengan metode artificial neural network (ANN) merupakan metode peramalan paling baik dari ketiga metode peramalan yang ada dan baik diimplementasikan di rumah sakit.

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A forecast is one of the important aspects of a company to achieve a good supply chain management system. The forecast could help a company to avoid overstock conditions and ensure the availability of the product. Based on that concept, forecasts could also be used to ensuring the availability of medicine stock in hospitals. The medicine itself is one of the sensitive and reactive materials that make medicines need a very intense inventory condition and couldn't keep in a long period of time. On the other hand, hospitals need to ensure the availability of each medicine. Based on that condition, it is undoubtedly true that the forecast is needed in the hospital supply chain to ensure medicine availability and avoid overstocking. This research will compare three different methods of forecasting, that is single exponential smoothing (SES), autoregressive integrated moving average (ARIMA), and artificial neural network (ANN). The goal of this research is to find and analyze the best forecasting method suitable for the hospital supply chain. Three medicines that will be analyzed in this research are Rhinofed, Simvastatin, and Betahistin based on their title as fast-moving drugs using 62 periods of historical sales. As a result, the artificial neural network method has the smallest error and creates a better accuracy compared to another two methods. Even if every single method has its own strengths and weaknesses, the artificial neural network is the best method among the three methods that been proposed and could be implemented in the hospital supply chain."

"ABSTRAK

Penelitian ini membahas tentang bullwhip effect yang memberikan pengaruh terhadap kegiatan dari operasional perusahaan yang berfokus kepada kegiatan di dalam rantai pasokan perusahaan dan meneliti aspek-aspek dari rantai pasokan yang dapat dipengaruhi oleh bullwhip effect dan aspek apa saja yang dapat dijadikan sebagai alat penilaian untuk mengukur kinerja rantai pasokan dari jaringan rantai pasokan. Hasil penelitian menemukan bullwhip effect memberikan pengaruh yang negatif kepada rantai pasokan dimulai dari hulu sampai ke hilir atau dari pemasok sampai ke konsumen akhir, sehingga perlu dimitigasi oleh perusahaan agar pada saat berjalannya proses operasional tidak mengalami gangguan penurunan kinerja rantai pasokan, serta memberikan aspek-aspek dari kinerja rantai pasokan yang bisa dioptimalkan oleh perusahaan untuk mendapatkan keunggulan kompetitif.

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ABSTRACT

This research discusses the bullwhip effect that influences the company operational activities that focus on activities in the company supply chain and examines aspects of the supply chain that can be influenced by the bullwhip effect and what aspects can be used as assessment tools to measure supply chain performance from the supply chain network. The results of the research found that the bullwhip effect had a negative influence on the supply chain starting from upstream to downstream or from suppliers to end-customers, so that it needed to be mitigated by the company so that during the operational process the supply chain does not experience a disruption in the supply chain, and provide aspects of supply chain performance that can be optimized by the company to gain a competitive advantage."

"Green supply chain (GSCM) adalah pendekatan yang muncul dalam manajemen rantai pasokan untuk mengurangi dampak lingkungan dari proses yang berkaitan dengan aliran barang dan material. Hal ini dianggap sebagai sistem kejadian diskrit. Salah satu alat yang memungkinkan untuk memodelkan sistem kejadian diskrit adalah jaring Petri. Sebuah model Colored Petri Net (CPN) dari model GSCM tersebut dikembangkan, alasan untuk menggunakan CPN daripada Petri nets biasa adalah karena memungkinkan pelekatan data (atau warna). Tesis ini mengembangkan model CPN untuk jaringan GSCM, dan memverifikasinya dengan menggunakan data sekunder dari penelitian lain sebagai studi kasus untuk membandingkan hasil simulasi rantai pasok ke depan. Setelah model tersebut terbukti serupa, dan oleh karena itu dapat mewakili rantai pasok yang sebenarnya. Model CPN diperluas menjadi CPN jaringan GSCM dengan menggunakan data yang sama dengan studi kasus. Hasil dari simulasi menunjukkan bahwa menerapkan reverse logistic dalam jaringan rantai pasok untuk menjadikannya sebagai jaringan GSCM adalah hal yang memungkinkan dan berpotensi menguntungkan perusahaan.

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Green supply chain is an emerging approach in supply chain management to reduce environmental impact of the process concerning the flow of goods and material. It is considered as a discrete-event system. One possible tool to model discrete-event systems is Petri nets. A Colored Petri Net (CPN) model of the said green supply chain model is developed, the reason to use a CPN rather than ordinary Petri nets is because it allows the attachment of data (or color). This thesis developed a CPN model for a GSCM network, and verify it by using a secondary data from another research as a case study to compare the results of the forward supply chain simulations. After the model is proven to be similar, and therefore representative of the real supply chain. The CPN model are expanded to be a GSCM network CPN using the same data as the case study. The results of the simulation indicated that implementing reverse logistic in a supply chain network to make it a GSCM network is possible and potentially beneficial to the company."

"Supply chain is a system in which an organization transfers products and services to the customers. This chain is actually a network of various entities from downstream to upstream which has different processes and activities, but to serve common purposes to create a value in the form of products or services to final customer.The shift in business landscape, such as market globalization, more demanding custOmers, and shorter product life cycle, has caused supply chain ag ility becom i ng o ne maj o r facto r th at d ete rm î n es corn p a ny? s corn petitive advantage.This report tries to describe the supply chain in Alcatel with focus in Mobile Network Division. it ¡s one among several business divisions inside Alcatel concerned with equipments for mobile network infrastructure as its main product. It will also cover the process along the chain, from headquarter in France, Indonesian? subsidiary and final customer.The supply chain description is concentrated in its main process and activities which are planning and customer?s order fulfillment. It also describes the information system used to support the process and exchange of information between parties involved. These aspects will be seen from the point of view of headquarter and from Indonesia?s subsdiary.The analysis of supply chain performance ¡s based on qualitative and quantitative analysis. The first will be based on supply chain drivers which are: transportation, information, inventory, and facilities. The seconnd is done by measuring some common metrics and compare them with targets internally set by Alcatel.From the observation and analysis done, ¡t can be concluded that Alcatel?ssupply chain performance has not reached ¡ts optimum level due to some reasons:-Planning process is becoming a weak point because it can not anticipate change or modificatIon in customer demands which create high inventory-Application of Alcatel?s standard supply chain process which has notreached supply chain?s entities in Indonesian subsidiary-Less concern for development of information system to support supplyChain"