A Study on Patent Storage Problems of Cooperation between Small and Micro Businesses and Universities in the Triple Helix of University-Industry-Government Relations — Based on Economic Order Quantity Model

2013 ◽  
Vol 712-715 ◽  
pp. 3149-3152 ◽  
Author(s):  
Pei Yu Tang ◽  
Shi Bin Su
Keyword(s):  
Triple Helix ◽  
Optimal Solution ◽  
Research Direction ◽  
Economic Order Quantity ◽  
Economic Order ◽  
Future Research ◽  
Order Quantity ◽  
Future Research Direction ◽  
Government Relations ◽  
University Industry

The paper uses Economic Order Quantity Model to analyze patent storage problems of cooperation between small and micro businesses and universities from the perspective of university-industry-government relations and reach a conclusion. The author obtains the optimal solution and points out the future research direction.

Economic Order Quantity Model with Innovation Diffusion Criterion under Influence of Price-Dependent Potential Market Size

2014 ◽  
Vol 11 (05) ◽  
pp. 1450028 ◽  
Author(s):  
K. K. Aggarwal ◽  
Alok Kumar
Keyword(s):  
Innovation Diffusion ◽  
Diffusion Theory ◽  
Optimal Solution ◽  
Economic Order Quantity ◽  
Economic Order ◽  
Market Size ◽  
Order Quantity ◽  
Eoq Model ◽  
Potential Market ◽  
Replenishment Policy

In last few decades various models developed under inventory control section whether of probabilistic or deterministic nature did not consider the effect of marketing parameters. The marketing parameters especially associated with innovation diffusion theory make the inventory models more realistic. In this paper, an inventory model has been proposed based on the explicit assumptions of interaction of marketing parameters to the optimal inventory replenishment policy. A time-dependent innovation driven demand has been incorporated in the basic economic order quantity (EOQ) model to know the realistic features of the model. This model assumes that potential market size is dynamic over time and is dependent on the price of the product. The model is illustrated with a numerical example and to know the effectiveness of the model a sensitivity analysis of the optimal solution with respect to different parameters has been performed.

An Economic Order Quantity Model for New Products When Demand Follows Dynamic Innovation Process

2014 ◽  
pp. 297-319
Author(s):  
K. K. Aggarwal ◽  
Alok Kumar
Keyword(s):  
Demand Function ◽  
New Products ◽  
Optimal Solution ◽  
Innovation Process ◽  
Life Cycles ◽  
Economic Order Quantity ◽  
Economic Order ◽  
Market Size ◽  
Order Quantity ◽  
Potential Market

In this era of globalization and constant innovation, the life cycles of products are diminishing, which tends to cause dynamic behaviour in the system, and because of this, there is a constant introduction of new products in the market. Therefore, while developing inventory models for new products, it becomes necessary to consider dynamic parameters associated with the demand function and responsible for making the system dynamic, which are essential for economic ordering policies for such products. In this chapter, an economic order quantity model is developed in which the demand is time-dependent and innovation-driven. The parameters such as coefficient of innovation and potential market size associated with the demand function are considered dynamic over time to match the real feature of the system. The model is illustrated with a numerical example, and a comprehensive sensitivity analysis of the optimal solution with respect to different parameters is performed to know the utility of the model.

scholarly journals Impact of Logistic Processes on Economic Order Quantity with Quantity Discount: An Optimization Approach

2020 ◽  
pp. 44-52
Author(s):  
Ágota Bányai ◽  
Béla Illés ◽  
Zhumatayeva Gaziza ◽  
Tamás Bányai ◽  
Péter Tamás
Keyword(s):  
Inventory Management ◽  
Optimal Solution ◽  
Economic Order Quantity ◽  
Economic Order ◽  
Optimization Approach ◽  
Quantity Discounts ◽  
Order Quantity ◽  
Logistics System ◽  
Materials Handling ◽  
Transportation Capacity

Inventory processes have significant importance in a company's logistics system and greatly influences its economic operation. Inventory management systems are used in the case of both dependent and independent products. The most used inventory model is the computation of economic order quantity model, which can be used in various types of objective functions and constraints. Logistic processes and their materials handling operations have a great impact on the optimal solution of economic order quantity problems, therefore it is important to consider logistic aspects while using EOQ. Within the frame of this article the authors describe a model considering available storage and transportation capacity, while fixed order lots as size of loading units and quantity discounts are taken into consideration. Two scenarios are discussed to validate the model and highlight the importance of logistics related constraints in computation of economic order quantity.

ANALISA SISTEM PERSEDIAAN BAHAN BAKU PADA INDUSTRI BINTANG PRIMA ACEH BESAR

2020 ◽  
Vol 8 (1) ◽  
Author(s):  
Chairul Amni
Keyword(s):  
Economic Order Quantity ◽  
Economic Order ◽  
Order Quantity

Perencanaan persediaan bahan baku merupakan salah satu peranan yang sangat penting dalam dunia industri untuk meningkatkan permintaan pasar. Sebuah perencanaan produksi akan berjalan dengan baik jika di dukung dengan adanya persediaan bahan baku yang memadai. Persediaan bahan baku juga memberikan kontribusi biaya yang cukup besar sehingga komponen biaya ini juga perlu untuk dikendalikan. Melihat pentingnya fungsi perencanaan produksi dan pengendalian persediaan bahan baku, maka perlu adanya usaha untuk mengelolanya secara efisien untuk mendapatkan hasil yang optimal. Perencanaan bahan baku merupakan hal yang sangat penting dilakukan untuk mendukung proses produksi, sehingga tidak terjadi masalah seperti keterlambatan pengiriman barang kepada konsumen, dan pemborosan biaya bahan baku. Tujuan dari penelitian ini adalah untuk mengetahui sistem pengendalian bahan baku yang diterapkan serta untuk mengetahui jumlah ekonomis bahan baku pada setiap kali pemesanan yang di analisis dengan menggunakan metode EOQ (Economic Order Quantity). Dari penelitian ini mendapatkan hasil yang menunjukkan bahwa penggunaan metode EOQ dalam pemesanan bahan baku jauh lebih optimal dan efisien dibanding metode yang selama ini diterapkan, terlihat dari selisih total biaya pemesanan bahan baku pada tepung mencapai 1,21% (404.950 rupiah) selisih pada bahan baku gula 0,02% (4.450 rupiah) dan selisih biaya pada pemesanan ragi dan garam sebesar 14,31% yaitu sebesar Rp. 82.500 untuk Ragi dan Rp. 8.250 untuk selisih pemesanan garam. dengan demikian dapat disimpulkan bahwa penggunaan metode EOQ mempuanyai hasil baik dalam melakukan pemesanan bahan baku sehingga bahan baku untuk produksi tidak mengalami penumpukan dan tidak mengalami kekosongan dalam gudang.

Analisis Pengendalian Persediaan Bahan Baku pada PT.Tri Agro Palma Tamiang

2017 ◽  
Vol 8 (2) ◽  
pp. 710-724
Author(s):  
Dewi Rosa Indah ◽  
Elsayus Yulia Risasti
Keyword(s):  
Economic Order Quantity ◽  
Economic Order ◽  
Order Quantity

Penelitian ini bertujuan untuk mengetahui sistem pengendalian persediaan bahan baku pada PT. Tri Agro Palma Tamiang. Metode analisis data yang digunakan adalah analisis kuantitatif dengan menggunakan metode Economic Order Quantity, stok pengaman dan titik pesan kembali. Berdsarkan hasil analisis Kuantitas pembelian yang optimum menurut kebijakan perusahaan adalah 248,78 Ton pertahun. Sedangkan berdasarkan metode Economic Order Quantity kuantitas pembelian yang optimum adalah 470,68 ton. Frekuensi pembelian yang optimum menurut kebijakan perusahaan adalah 312 kali, sedangkan dengan menggunakan metode Economic Order Quantity yaitu 165 kali. Total biaya persediaan dengan menggunakan kebijakan perusahaan adalah Rp.5.425.172 setelah menggunakan metode Economic Order Quantity dapat mengefisiensikan besarnya biaya persediaan perusahaan yaitu Rp. 4.482.274. Sementara itu untuk persediaan pengaman dan titik pemesanan kembali menurut kebijakan perusahaan tidak ada, sedangkan menurut perhitungan metode Economic Order Quantity besarnya persediaan pengaman adalah sebanyak 1.106,74 Ton dan titik pemesanan ulang sebesar 1.355,52 Ton.

ANALISIS PENGENDALIAN PERSEDIAAN BAHAN BAKU BENANG PADA PRODUK UNDERWEAR DENGAN METODE EOQ (Studi Kasus pada PT. Indonesia Wacoal)

2019 ◽  
Vol 14 (1) ◽  
pp. 1
Author(s):  
Rizki Ahmad Fauzi ◽  
Rudi Hartono
Keyword(s):  
Economic Order Quantity ◽  
Economic Order ◽  
Order Quantity

Mengendalikan persediaan dengan tepat bukanlah hal yang mudah. Jumlah persediaan yang terlalu besar akan mengakibatkan timbulnya dana yang dikeluarkan menjadi terlalu besar, selain itu resiko kerusakan bahan baku juga menjadi lebih besar. Namun bila persediaan terlalu sedikit akan mengakibatkan terjadinya kekurangan persediaan yang menghambat proses produksi. Metode pengendalian persediaan yang dibandingkan dalam penelitian ini yakni metode Economic Order Quantity (EOQ). Penelitian ini bertujuan mengetahui pengendalian persediaan bahan baku benang ada PT. Indonesia Wacoal yang efektif dan efisien agar tercapai hasil produksi yang optimal menggunakan metode Economic Order Quantity (EOQ). Metode EOQ adalah metode perhitungan yang mengidentifikasi kuantitas pemesanan atau pembelian optimal dengan tujuan meminimalkan biaya persediaan yang terdiri dari biaya pemesanan dan biaya penyimpanan. Perhitungan data yang digunakan adalah data mulai tahun 2014 hingga Agustus 2016. Hasil penelitian yang dilakukan menunjukan bahwa total biaya persediaan bahan baku benang polina polina yang harus dikeluarkan perusahaan lebih besar bila dibandingkan dengan total biaya persediaan yang dihitung menurut metode EOQ. Terjadi penghematan pada tahun 2014 pada benang polina 110 (998) sebesar Rp 3.760.889 tahun 2015 sebesar Rp 2.565.837 dan tahun 2016 sebesar Rp 10.993.200. Pada tahun 2014 pada benang polina 110 (999) sebesar Rp 2.225.378 tahun 2015 sebesar Rp 1.857.287 dan tahun 2016 sebesar Rp 3.928.178. pada tahun 2014 pada benang polina 110 (997) sebesar Rp 3.959.323 tahun 2015 sebesar Rp 4.874.495 dan tahun 2016 sebesar Rp 6.117.023. Kata kunci: Bahan Baku, Economoic Order Quantity, Persediaan

Giải pháp hợp tác giữa trường đại học điện lực và doanh nghiệp trong việc đào tạo kỹ năng nghề cho sinh viên

2018 ◽  
Vol 34 (1) ◽  
Author(s):  
Nguyen Thi Thanh Dan
Keyword(s):  
Triple Helix ◽  
Vocational Skills ◽  
Government Relations ◽  
World Economic ◽  
Competency Based ◽  
Social Partnerships ◽  
Market Needs ◽  
Global Agenda ◽  
University Industry ◽  
And Training

  The purpose of the paper is to research some solutions of cooperation between universities and enterprises in training vocational skills for students. Through the survey on assessment of vocational skills of students and the need for cooperation between Enterprises and Electric Power University, the research proposes some solutions  between two elements of the mechanism of cooperation between University  and Enterprises in training vocational skills for students to ensure graduates can meet the requirements of recruitment agencies as well as the requirements of socio-economic development and employment. Keywords Volcational skill, cooperation, universities, enterprises, Electric Power University References [1] Mạnh Xuân, Gắn kết trường đại học và doanh nghiệp trong đào tạo nhân lực, Nhân dân điện tử, 2015. http://www.nhandan.com.vn/giaoduc/tin-tuc/item/25807602-gan-ket-truong-dai-hoc-va-doanh-nghiep-trong-dao-tao-nhan-luc.html [2] Nguyễn Đình Luận, Sự gắn kết giữa nhà trường và doanh nghiệp trong đào tạo nguồn nhân lực phục vụ phát triển kinh tế xã hội ở Việt Nam: Thực trạng và Khuyến nghị, Tạp chí Phát triển và hội nhập, số 22 (32), Tháng 5-6/2015.[3] Nguyễn Thị Thanh Dần, Động lực hợp tác giữa nhà trường và doanh nghiệp trong việc nâng cao kỹ năng nghề cho sinh viên, Tạp chí giáo dục, Số đặc biệt 11/2016[4] Nguyễn Tiến Long, Phạm Hồng Hạnh. Xây dựng kho dữ liệu kĩ thuật, ứng dụng cho nghiên cứu khoa học và dạy học tại trường sư phạm kỹ thuật – đạo tạo nghề. Tạp chí khoa học giáo dục, số 338 kì 2 (7/2014) [5] Trịnh Thị Hoa Mai, Liên kết đào tạo giữa trường Đại học với doanh nghiệp ở Việt Nam, Tạp chí Khoa học Đại học Quốc gia Hà Nội, Kinh tế - Luật 24 (2008), 30-34[6] Vũ Thị Phương Anh, Liên kết đào tạo giữa nhà trường và doanh nghiệp thiếu mắt xích quan trọng, Báo Nhân dân cuối tuần, 2013. http://www.nhandan.com.vn/cuoituan/chuyen-de/item/21342502-thieu-mat-xich-quan-trong.html[7] Competency-based training, TAFE Queensland, 03 December, 2008, http://www.tafe.qld.gov.au/courses/flexible study/ competencv.html. [8] Croissant, J.L., Smith-Doerr, L. (2008). Organizational Contexts of Science: Boundaries and Relationships between University and Industry. In: Hackett, Edward J.; Amsterdamska, O., Lynch, M., Wajcman, J. (eds.): The Handbook of Science and Technology Studies, 3rd edition. Cambridge u.a.: The MIT Press, pp. 691-718 [9] Dalley, Stephanie and Peter Oleson (2003).“Senacherib, Archimedes, and the Water Screw: The Context of Invention in the Ancient World”, Technology and Culture vol. 44 no. 1, pp. 1–26. 
[10] Davos Kloster (2014), Matching skills and labour market needs – Building social partnerships for better skills and better jobs, Global Agenda Council on Employment, World Economic Forum.[11] Davos Kloster (2014), Matching skills and labour market needs – Building social partnerships for better skills and better jobs, Global Agenda Council on Employment, World Economic Forum.[12] Dzisah, J. & Etzkowitz, H., (2008): Triple Helix Circulation: The Heart of Innovation and Development, International Journal of Technology Management and Sustainable Development, 7(2), pp. 101-115 [13] Etzkowitz, H., Leydesdorff, L. (2000): The Dynamics of Innovation: From National Systems and “Mode 2” to a Triple Helix of University-Industry-Government Relations. In: Research Policy, 29, pag. 109-123 [14] Harris, R., Guthrie, H., Hobart B., & Lundberg, D. (1995). Competency based education and training: Between a Rock and a Whirlpool. South Melbourne: Macmillan Education Australia.[15] Henry Etzkowitz (2008). The triple helix: university-industry-government innovation. Routledge
270 Madison Ave, New York, NY 10016, ISBN 0-203-92960-8 Master e-book ISBN [16] Jones, L., & Moore, R. (1995). Appropriating competence. British Journal of Education and Work, 8(2) 78-92[17] Kathleen Santopietro Weddel (2006), Competency Based Education and Content Standards, Northern Colorado Literacy Resource Center, USA.[18] Leydesdorff, L., Etzkowitz, H. (1996): Emergence of a Triple Helix of University-Industry-Government Relations, Science and Public Policy, 23, pp.279-286. [19] Mihaela & Cornelia Dan (2013). Why Should University and Business Cooperate? A Discussion of Advantages and Disadvantages, International Journal of Economic Practices and Theories, Vol. 3, No. 1, 2013 (January), e-ISSN 2247–7225 [20] Paprock, K. E. (1996) Conceptual structure to develop adaptive competencies in professional. IPN Ciencia Are: Cultura, Nueva Epoca, 2 (8), 22-25.[21] Perkmann, M. (2007): University-industry relationships and open innovation: towards a research agenda. International Journal of Management Reviews, 9 (4), pp. 259–280 [22] Robert E. Norton: Dacum Handbook. Center on Education and training for Employment – College of Education – The Ohio State University, 1997.[23] Shirley Fletcher (1995). Designing Competence-based Assessment in the Professions in Australia, Assessment in Education: Principles, Policy & practice, Volume1, Issue 1.[24] Urayaa, E. (2010). Conceptualizing the Regional Roles of Universities, Implications and Contradictions, European Planning Studies, 18(8), pp. 1227-1246

Analisis Perbandingan Teknik Peramalan Kebutuhan Obat Dengan Metode Arima Dan Single Eksponensial Smoothing Studi Kasus: Rsud Indramayu

2019 ◽  
Vol 5 (1) ◽  
Author(s):  
Ilan Aliasi Zahra
Keyword(s):  
Time Series ◽  
Economic Order Quantity ◽  
Economic Order ◽  
Order Quantity

Ketersediaan obat menjadi hal utama pada suatu layanan kesehatan. Fluktuasi pemakaian obat-obatan yang terjadi setiap tahun menjadi kendala bagian gudang obat dalam perencanaan pengadaan di rumah sakit. Peramalan (forecasting) merupakan alat bantu yang penting dalam pembuatan perencanaan bagi setiap organisasi maupun instansi yang membutuhkan. Penting bagi rumah sakit membuat perencanaan persediaan obat untuk mengatasi permasalahan berkaitan dengan ketersediaan alat kesehatan maupun obat-obatan. Tujuan dari penelitian ini yaitu untuk meramalkan kebutuhan obat dengan menggunakan teknik-teknik forecasting dan perhitungan nilai Economic Order Quantity. Sebuah forecasting atau tekik peramalan diperlukan, untuk memprediksi kebutuhan obat-obatan pada masa mendatang. Metode yang digunakan pada penelitian ini yaitu peramalan time series Arima untuk proses pengambilan prediksi dan perhitungan EOQ. Hasil penelitian ini berupa nilai peramalan kebutuhan obat untuk satu periode mendatang ditunjukan dengan nilai eror model peramalan yang paling kecil, yaitu ARIMA (1.0.0) dengan nilai eror sebesar 13%, serta hasil perhitungan Economic Order Quantity untuk kebutuhan obat pada periode mendatang.

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