scholarly journals Penerapan Program Linear Fuzzy dalam Optimalisasi Jumlah Produksi dan Keuntungan di K-Bakery

2021 ◽  
Vol 1 (2) ◽  
pp. 36
Author(s):  
Nelita Anggraini Sitanggang ◽  
Mira Mustika
Keyword(s):  
Production Planning ◽  
Raw Materials ◽  
Linear Program ◽  
Raw Material ◽  
Market Demand ◽  
Safety Stock ◽  
Material Resources ◽  
Maximum Profit ◽  
Limited Supply ◽  
Brown Bread

K-Bakery is a bakery located in Bandar Lampung City, Lampung. K-Bakery produces various types of bread, namely brown bread, nuts, greentea, mocha, and tiramisu bread which involve various raw material resources. Unstable market demand creates obstacles for K-Bakery in formulating the number of each type of bread to be produced so as to produce maximum profit. However, in determining the amount of production must pay attention to the limited supply of raw materials. In this case, there is a need for production planning so that all available resources can be used optimally and produce a combination of production that provides maximum profit. One way to solve this problem is to optimize production using a fuzzy linear program with a tolerance of 10% as the capability of K-Bakery. The use of the fuzzy linear program generates greater profits than the usual linear program, the profit obtained is Rp. 11.247.972,1708by producing 320 chocolate breads, 449,75 peanut breads, 365,667 greentea breads, 250 moka breads fruit, 449,925 srikaya bread, and 499,975 tiramisu breads. In addition, the value of l = 0,5 is obtained, or in other words, the maximum addition of each raw material is 50% of the available safety stock.

scholarly journals PERENCANAAN BAHAN BAKU DAN HASIL PRODUKSI MENGGUNAKAN METODE LINIER PROGRAMMING SIMPLEK

2017 ◽  
Vol 12 (2) ◽  
Author(s):  
Monika Handayani ◽  
Eka Kusuma Dewi
Keyword(s):  
Linear Programming ◽  
Production Planning ◽  
Simplex Method ◽  
Raw Materials ◽  
Raw Material ◽  
Planning System ◽  
Testing System ◽  
Basic Solution ◽  
Linear Programming Method

<p>CV. Baja Utama Landasan Ulin is a business entity that manufactures various products using the basic ingredients of iron. In the management of raw materials for the production of common regulatory process raw materials into sections for further processing. This setting is often done manually without doing careful planning, so that at the end of each production process there are many remaining pieces of the raw materials that should be used in production. In addition to the determination of the production is necessary to reference how the product should be made for each type of existing products. This is often an important factor that pushed for the optimization of production planning in determining the number of products for each type of product and raw material consumption.Linear Programming is one of the methods used in production planning to regulate the use of raw materials is limited. Simplex method is part of the linear programming method that can be used in the production planning system implementation. Simplex method identifies an initial basic solution and then move systematically to other basic solution that has the potential to improve the value of the objective function.The calculation result of production planning using the simplex method can be used as a reference in the decision making production planning. By building an application using the simplex method can assist in the calculation of production peencanaan more efficiently and effectively. Accuracy testing system constructed show significant results with great value reached 94% level of accuracy.<br />Keywords: simplex, production planning, the maximum gain, linear programming</p>

scholarly journals ANALYSIS CONTROL SUPPLIES RAW MATERIALS TO EFFICIENCY COST, USING THE METHOD OF ECONOMIC QUANTITY ORDER AT CV. PQR

2018 ◽  
Vol 1 (01) ◽  
pp. 41
Author(s):  
Wartoyo Hadi
Keyword(s):  
Production Process ◽  
Raw Materials ◽  
Analysis Data ◽  
Raw Material ◽  
Economic Order Quantity ◽  
Economic Order ◽  
Order Quantity ◽  
Safety Stock ◽  
Reorder Point ◽  
Efficiency Cost

The purpose of the implementation of this research is to find the effectiveness of supplies raw materials, the method of analysis data used in the square is the smallest trend for planning raw materials and controling supplies use method of economic order quantity (EOQ) analyze reorder point. Analysis reorder point and safety stock. And analyzes efficiency cost of raw materials. Forecasting raw materials years 20x7 according to the smallest trend, cloth and dakron happened the difference is greater than of the target needed (according to a company); controling supplies raw materials with the methods eoq in 20x7 more effective than reservations raw materials cloth and dakron and more efficient than cost raw materials. The company should review the policy of forecasting raw material supplies that had been undertaken and make planning supplies the raw material that more accurate using the firm’s historical data and not only targeting the output production next year, so that machines production can be optimized. Considering the use of control supplies with the methods economic order quantity to companies, so this analysis can determine material reservations, supplies safety, maximum supplies to avoid the risk of running out of raw materials, because the companies often happened less dressed up a result of reservations that time is inaccurate, the lack of safety stock and the deferred the delivery of goods which often disturb the production process, by this method can prevent these things, so that the production process can run smoothly and minimize the cost of raw materials supplies.

Production Planning Based on DEA Profit Efficiency Models

2017 ◽  
Vol 4 (3) ◽  
pp. 1-14
Author(s):  
Feng Liu ◽  
Mengni Zhang
Keyword(s):  
Production Planning ◽  
Operations Management ◽  
Airline Industry ◽  
Data Envelopment ◽  
Market Demand ◽  
Profit Efficiency ◽  
Optimal Output ◽  
Maximum Profit ◽  
Production Possibility Set ◽  
Output Constraint

In this research, the authors propose DEA (data envelopment analysis) profit efficiency models for production planning which is one of important problems in the production and operations management. Different from traditional models, the constraint that the optimal output is supposed to be not less than the original one from the production possibility set is omitted in their developed no output constraint maximum profit (NOCMP) model. Besides, observing that output prices could be varied with the total market demand in the market, the researchers present the no output constraint maximum profit with varied output price (NOCMP-VOP) model. The authors apply these two DEA profit efficiency models to U.S. airline industry for illustration. The developed NOCMP and NOCMP-VOP models in this study contribute to developments of both the DEA profit efficiency model and its applications.

scholarly journals Mapping of raw materials and habitats in the Danish sector of the North Sea

1969 ◽  
Vol 23 ◽  
pp. 33-36
Author(s):  
Jørn Bo Jensen ◽  
Sara Borre ◽  
Jørgen O. Leth ◽  
Zyad Al-Hamdani ◽  
Laura G. Addington
Keyword(s):  
North Sea ◽  
Raw Materials ◽  
Distribution Volume ◽  
Raw Material ◽  
Marine Strategy Framework Directive ◽  
Material Resources ◽  
The North ◽  
General Mapping ◽  
The North Sea ◽  
Substrate Types

In the summer of 2010, the Geological Survey of Denmark and Greenland (GEUS) mapped the potential raw materials and substrate types, over large parts of the Danish economic sector of the North Sea, in cooperation with Orbicon A/S. The mapping was carried out for the Danish Nature Agency; it is part of the general mapping of raw material resources within the territories of the Danish state and forms part of the input for the implementation of the European Union’s Marine Strategy Framework Directive. The purpose was (1) to provide an overview of the distribution, volume and composition of available raw materials and (2) to identify, describe and map the distribution of the dominant marine bottom types.

scholarly journals Circular investments as a key to solving the growth dilemma

2021 ◽  
Vol 188 (3-4) ◽  
pp. 58-68
Author(s):  
Ludmila Kormishkina ◽  
◽  
Evgenii Kormishkin ◽  
Vladimir Gorin ◽  
Dmitrii Koloskov ◽  
...  
Keyword(s):  
Raw Materials ◽  
Multiple Linear Regression Model ◽  
Raw Material ◽  
Household Waste ◽  
Negative Effects ◽  
Methodological Foundation ◽  
Material Resources ◽  
Real Gdp ◽  
Scientific Hypothesis

The rationale for this study is based on the extreme importance of finding a solution to a complex growth dilemma arising from the negative effects of human activity and the limited ability of the ecosystem to regenerate and provide resources required by mankind to ensure sustainable development and the long-term prosperity. The research is aimed at proving a scientific hypothesis that states: when the global raw-materials crisis becomes increasingly noticeable in various countries of the world, including Russia, circular investments may become a driver for long-term economic growth and the launch of far-reaching reforms of the economy in the 21st century. Circular investments in this paper are viewed as a special type of real eco-investment that combines advancements in technology and innovations to ensure renewal and industrial-scale reproduction of resources (raw materials and energy) from industrial and household waste, along with the mitigation and/or elimination of negative effects, on the environment. A multiple linear regression model has been developed to confirm a statistically-relevant connection between circular investments and real GDP. As a methodological foundation for the model, we used the classic Cobb-Douglas production function modified to take into account industrially reproduced raw material resources included in the production process. Further, we have defined major limits for circular investments in Russia today and highlighted the primary measures which are to be taken to launch circular investments in order to find a solution to the complex growth dilemma.

scholarly journals SME INTER-CLUSTERING LINKAGE OF EAST JAVA: AMONG BUSINESS STRATEGY AND COOPERATIVES

2021 ◽  
Vol 6 (2) ◽  
pp. 174
Author(s):  
Deni Aditya Susanto
Keyword(s):  
Business Strategy ◽  
Business Performance ◽  
Raw Materials ◽  
Descriptive Analysis ◽  
Raw Material ◽  
Matrix Analysis ◽  
Material Resources ◽  
Business Units ◽  
Swot Matrix ◽  
Strategy Variables

The Indonesian SME cluster has not fully implemented the cluster concept, causing the SME cluster to stagnate. The Meubel SME Cluster of Pasuruan City and Malang City are two prime clusters working to show their economic crisis performance several times. This study aims to examine the factors of inter-firm linkage and business strategy on business performance. Methodologically, this study uses several analytical methods, namely multiple linear regression, to measure the influence between inter-firm linkage and business strategy variables on business performance, SWOT matrix to map strategy, and descriptive analysis to present non-parametric findings. This study analyzed 60 samples of MSEs from a population of 350 business units. The results of the study mentioned that aspects of business strategy (finance, marketing, human resources, research, development, and operations) had a more significant effect on business performance (sales, profits, assets, labor, and productivity) than inter-firm linkage (backward, forward, and horizontal). Through SWOT matrix analysis, the inter-clustering linkage of Malang City and Pasuruan cluster SMEs is naturally created. Access to raw materials and labor in the city of Malang began to be complicated even though consumers’ potential from large tourists and access to adequate technology. In contrast, Pasuruan City is lt to do marketing because of geographical conditions’ weakness even though the raw material resources and labor are abundant. The specialization of production is created with Pasuruan City as the production base and Malang City as the Marketing Base.Keywords: Cooperatives, Business Strategy, Inter-Clustering LinkageJEL: Q13, L21, C38

scholarly journals Monte Carlo Simulation and Scenario Analysis Based Limestone Quarry Production Planning

2021 ◽  
Vol 12 (1) ◽  
pp. 41-45
Author(s):  
Kausar Sultan Shah ◽  
Safi Ur Rehman
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Chemical Composition ◽  
Production Planning ◽  
Scenario Analysis ◽  
Raw Materials ◽  
Raw Material ◽  
Mix Design ◽  
Efficient Planning ◽  
The Impact

The key factor behind raw mix design in the cement factory is the appropriate production planning, resulting in high-quality raw material. Quarry managers usually come up with uncertainty-related raw materials due to variations in chemical composition. These uncertainties required efficient planning in terms of useful insight into this problem. This research provides a detailed explanation of scenario analysis of raw materials used in cement manufacturing using Monte Carlo simulation (MCS) and indices. Scenario analysis is used to predict the possibility of best, worst and most likely cases of raw material’s quality. Whereas, Monte Carlo simulation is used to evaluate the inherent uncertainty associated with chemical composition values in order to analyze the impact of truly unpredictable scenarios. The predictive results help in decisions related to production planning, raw mix design optimization and increasing the probability of designing the best plan.

scholarly journals Analisis Persedian Bahan Baku, Reorder Point dan Safety Stock Bahan Baku ADC-12

2020 ◽  
Vol 20 (2) ◽  
pp. 675
Author(s):  
Hazimah Hazimah ◽  
Yongki Antoni Sukanto ◽  
Nurlinda Ayu Triwuri
Keyword(s):  
Raw Materials ◽  
Raw Material ◽  
Economic Order Quantity ◽  
Order Quantity ◽  
Safety Stock ◽  
Reorder Point ◽  
Calculation Results ◽  
Descriptive Approach ◽  
Quantitative Descriptive ◽  
Optimal Calculation

The production process is very dependent on the availability of raw materials. An optimal calculation of raw material inventory is needed so that the company avoids the problem of lack or over stock of raw materials. This research aims to find out the quantity of raw material inventory, safety stock, and reorder point for ADC-12 raw materials.. This research uses a quantitative descriptive approach. Data sources obtained directly from the company. Analysis of the data used using the Economic Order Quantity method. Based on research and calculation results that have been done, if the company uses the EOQ method the quantity of raw material inventory is 80,861 kg. The quantity of the safety stock is 2,768 kg with a reorder point (ROP) of 14,038 kg.

scholarly journals ANALISIS BIAYA PERSEDIAAN BAHAN BAKU IKAN DAN PERHITUNGAN ECONOMIC ORDER QUANTITY (EOQ) PADA RUMAH MAKAN IKAN BAKAR KINAMANG

2018 ◽  
Vol 13 (02) ◽  
Author(s):  
Melinda Miranda Wijaya ◽  
David P. E. Saerang ◽  
Meily Y. B. Kalalo
Keyword(s):  
Raw Materials ◽  
Raw Material ◽  
Economic Order Quantity ◽  
Economic Order ◽  
Order Quantity ◽  
Inventory Cost ◽  
Safety Stock ◽  
Purchase Order ◽  
Reorder Point ◽  
The Cost

            The cost of raw material inventory is a sacrifice of economic resources, measured in units of money, which have occurred or are likely to occur for raw material inventory, consisting of purchase costs, storage costs, and inventory shortage. This study aims to determine (1) Total Inventory Cost (TIC) based on RM policy. Kinamang Fuel Fish and Economic Order Quantity (EOQ) method during 2017 (2) Frequency of ordering of efficient fish raw material during 2017 (3) Quantity of safety stock and when to reorder point of raw materials fish in RM. Ikan Bakar Kinamang during 2017. This research is a descriptive research with qualitative approach. And use case study method. The result of the research shows that the Cost of Fish Raw Material Supplies at Kinamang Fuel Fish Restaurant is still not economical because the purchase (order) is only based on the previous sales estimate, and does not take into account economically the expenses incurred for the purchase and storage of fish raw materials the. Precisely with the calculation of Economic Order Quantity (EOQ), the cost of raw materials inventory of fish is much less, and can determine properly and correctly about the safety stock (safety stock), and reorder (reorder point).Keywords: Inventory Cost, EOQ, Frequency, Safety Stock, ROP

scholarly journals Integrasi Linear Regression dan Aggregate Planning untuk Perencanaan dan Pengendalian Produksi Leaf Spring Hino OW 190/200 di Industri Komponen Otomotif

2021 ◽  
Vol 13 (2) ◽  
pp. 245
Author(s):  
Deni Ahmad Taufik ◽  
Indra Setiawan ◽  
Muhammad Wahid ◽  
Abdul Rochim ◽  
Muhammad Tosin
Keyword(s):  
Linear Regression ◽  
Production Planning ◽  
Raw Materials ◽  
Raw Material ◽  
Leaf Spring ◽  
Linear Regression Method ◽  
Planning And Control ◽  
Automotive Assembly ◽  
And Control ◽  
Material Requirements

Production planning and control in a manufacturing company involves all production activities from raw material requirements to finished products. The Jakarta Automotive Components Industry is engaged in manufacturing which produces leaf spring products that are sent to several regular customers, namely the Automotive Assembly Industry. Leaf spring Hino OW 190/200 is the type of spring ordered and shipped to PT. HMMI. Based on data for the January-December 2019 period, the demand for Hino OW 190/200 leaf spring has fluctuated quite significantly. The purpose of this study was to plan and control the production process of Leaf Spring Hino OW 190/200. Forecasting for the next 12 periods is based on demand plots from the previous 12 periods, calculating the Aggregate production plan, determining the Master Production Schedule (MPS), calculating raw material requirements using the Hybrid and Lot for Lot methods. The results showed that to support the smooth production, it can be seen that the production planning for forecasting calculations using the Linear Regression method generates a model Y=319,575+3,723X. Calculation of the need for main raw materials and components in 2020 uses the Hybrid and Lot for Lot method, which is 256,182.88 kg, much smaller than the company's calculations based on 2019 data, namely 259,827.40 kg.

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