Optimal Number Of Products Research Articles

Increasing Line Efficiency By Using Line Balancing In A Steel Manufacturing Company

Line balancing using the Takt Time method is recognized as a modern tool forassisting businesses in reducing costs and increasing profits. It is possible for the enterpriseto smoothly produce the most optimal number of products by rational calculation andresource arrangement. This paper presents a case study on the application of line balancingby the Takt Time method in a steel factory in Vietnam. The methods selected for the studyinclude describing the current situation of the factory, applying Lean Manufacturingimprovement tools, applying modern equipment technology, and rearranging factoryresources, finally calculating Line Balancing metrics and implementing them in practice.According to the findings of the research, using the Takt Time line balancing methodprovides numerous benefits to the factory. The number of operators decreased by 9 people.The percentage of line balance increased by 22% from 77% to 99% and the efficiency ofline balance increased by 6% from 93% to 99%. In addition, the study also helpsVietnamese businesses have a more objective view of the application of Takt Time linebalancing in the future.

Analisis Optimalisasi Keuntungan dengan Integer Linear Programming (ILP) dan Metode Branch and Bound pada UMKM RM Selera

A business such as MSMEs often experiences many obstacles or problems that hinder it in achieving its business goals. One of these problems is how to get the maximum profit by optimizing the product to be produced. Basically, the main purpose of building a business is to get enough profit or profit as much as possible. Optimization problems are part of society's problems, especially those engaged in the production business. Optimization is to minimize production costs and maximize sales revenue. This study aims to determine the most optimal number of products and maximize profits in optimizing Ayam Goreng production at RM Selera SMEs using the Integer Linear Programming simplex method and continued with the Branhc and Bound method. The results get with the addition of constraints 𝑥1 ≤ 0 obtained results X1 = 0 and X2 = 2 while with constraints 1 1 obtained results X1 = 1 and X2 = 1.5. The optimum integer solution has been obtained, namely the result of LP - 4 with X1 = 0 and X2 = 2. The maximum profit obtained for the Ayam Goreng Sambal Pecel and Ayam Goreng Sambal Rica at RM Selera SMEs is Rp.1.900.000.

Optimization Of Chicken Feed Production Using Goal Programming Method At PT. Japfa Comfeed Indonesia Tbk. Unit Makassar

PT Japfa Comfeed Indonesia Tbk is one of the largest and most integrated agri-food companies in Indonesia. The company's main business units are the manufacture of animal feed, chicken breeding, poultry processing, and agricultural cultivation. This company will automatically continue to increase its production results both in terms of quantity and in terms of quality to be able to compete in the market so that it can expand market share and offer products at affordable costs for consumers. At present, business progress is strongly influenced by fluctuations and variations in consumer demand. This also has an impact on the production of chicken feed carried out by PT Japfa Comfeed Indonesia Tbk Makassar unit. With the increasing demand for chicken feed, an effort is needed so that the production process runs according to available and profitable resources. This research aims to determine the optimal amount of production to generate optimal company profits. The method used in this study is the goal programming method because it can solve problems optimally with more than one goal. The results of this research show that the product of goal programming optimization is more profitable than the companies. The results obtained from this research are the optimal number of products is 4,967,155 kg, and the minimum production cost is Rp. 1,382,685,942,075, and the sales profit is Rp. 314,569,267,925 for a period of one year.

OPTIMASI PEMAKAIAN JAM KERJA DAN BAHAN BAKU DALAM MEMPRODUKSI MINUMAN INSTAN TRADISIONAL

CV. Cihanjuang Inti Teknik is a small or medium-sized business (UKM) engaged in the traditional beverage processing industry. The company is faced with problems of use to optimize the use of work time so that there is no idle work time or overtime working hours. Other problems, so far the procurement of raw materials carried out is also only based on estimates, namely with raw materials made in stock without taking into account quantitative calculations. The goal programming method is used with the aim of analyzing and describing the optimal use of resources in working hours and raw materials from the average production target needed by the company. The calculation of goal programming is supported by using LINDO (Linear Interactive Discrete Optimizer) program to obtain the optimal number of products from working hours and raw materials needed by the company. The results of the study obtained optimal regular working hours in scenarios I, II, III, and IV respectively in the amount of 159.95 hours/month, 174.25 hours/month, 176.26 hours/month and 192.37 hours/month. There was also an increase in the use of raw materials for ginger, coffee, ginseng and pepper in scenario II, raw materials for ginger, white and vanilla sugar in scenario III, raw materials for white sugar, vanilla and cinnamon in scenario IV.

OPTIMALISASI PRODUKSI MENGGUNAKAN METODE INTEGER PREEMPTIVE GOAL PROGRAMMING (Studi Kasus: UD Citra Ayu Bali)

One of the home industry in Bali that produces beauty products is UD Citra Ayu Bali. This company has five types of body scrub scent, where the five types of body scrub has a different number of requests. UD Citra Ayu Bali has been doing production activities only when there is demand, so the production process is still less than optimal because it is still done randomly or unplanned. Therefore, this research is done to make production planning body scrub UD Citra Ayu Bali by determining the prediction of the number of products that must be produced every week so that the production process becomes optimal. By using the integer preemptive goal programming method, the optimal production number of the five types scrubs for 12 consecutive weeks is 212 pieces, 548 pieces, 328 pieces, 474 pieces, 506 pieces, 455 pieces, 103 pieces, 381 pieces, 63 pieces, 547 pieces, 59 pieces, and 454 pieces.

Optimization of saving production cost in plastic jute sacks with dynamic programming

The plastic jute sack is one of the most popular rice packaging products in the market. One type of plastic jute sack used is LDPE type. The LDPE sacks used for rice packaging often-experiencing fluctuations in market demand. Fluctuating demand is a certain problem for companies in determining the number of production to meet the demand. It can be seen from the frequent over production companies and stock out at each period. Overproduction problem has an impact to increase production costs. Stock resulted in lost sales experienced adversely affected the company, especially from production cost. Based on the problems, the company must immediately performs an optimal production planning to handle various problems in the company. One method for saving the optimal cost production can be used is dynamic programming. This method aims to obtain the optimal number of production accordance to market demand. This research is done to reduce cost by optimizing number of production. Method that used to solve the problem is dynamic programming. By using this method, the company will obtain optimum production number with minimum production cost and considering total capacity available of the company. From the dynamic programming results obtained optimal production number with cost savings about 2.1%.

Perishable Inventory Management in Healthcare

This study addresses a problem encountered in a nation-wide, large-scale healthcare supply chain that comprises several hundred medical organizations (hospitals, clinics, pharmacies, etc.) and provides highly advanced medical care to several million people. The medical products in the system are perishable, meaning that they become unusable beyond a certain expiry date. It is necessary to track the ages of units in stock and to plan and control the inventory accordingly. The models developed herein represent a multi-echelon, multi-supplier inventory system and unite together aspects of perishability and outsourcing under deterministic demand for medical products, which include both perishable and deteriorating goods. The objective of the study is to determine the optimal number of products to be purchased from regular and outsource suppliers so as to meet the required demand at the minimum operating cost. The solution is a network-flow model that can be used to determine the trade-off between the quantities of items to be ordered from the two types of suppliers in each time period. In addition, the study analyzes different distribution policies to account for the perishable nature of the products. Further insights are obtained by applying the model to a case study of a real-life healthcare supply chain from which interesting results are drawn.

Modelling the customer relationship management in a multi-layer supply chain considering product life cycle

We are aiming to develop a mathematical model in a three layer supply chain using customer relationship management extracting the product life cycle factors to satisfy customers’ interests. Then, the mathematical model implies the optimal number of products and the fulfillment of an activity. We consider a three layer supply chain consisting supplier, manufacturer and customers. Customers’ opinions about the product life cycle are collected via a customer relationship system. The problem is modelled to minimise the total cost of the system and maximise the process capability. The proposed bi-objective model was handled using analytic hierarchy process (AHP) weighing method. Also, a linearisation is performed to facilitate optimisation process. An application example is illustrated to verify the effectiveness of the proposed methodology.

Enhancing marketing with engineering: Optimal product line design for heterogeneous markets

Successful product line design and development often require a balance of technical and market tradeoffs. Quantitative methods for optimizing product attribute levels using preference elicitation (e.g., conjoint) data are useful for many product types. However, products with substantial engineering content involve critical tradeoffs in the ability to achieve those desired attribute levels. Technical tradeoffs in product design must be made with an eye toward market consequences, particularly when heterogeneous market preferences make differentiation and strategic positioning critical to capturing a range of market segments and avoiding cannibalization. We present a unified methodology for product line optimization that coordinates positioning and design models to achieve realizable firm-level optima. The approach overcomes several shortcomings of prior product line optimization models by incorporating a general Bayesian account of consumer preference heterogeneity, managing attributes over a continuous domain to alleviate issues of combinatorial complexity, and avoiding solutions that are impossible to realize. The method is demonstrated for a line of dial-readout scales, using physical models and conjoint-based consumer choice data. The results show that the optimal number of products in the line is not necessarily equal to the number of market segments, that an optimal single product for a heterogeneous market differs from that for a homogeneous one, and that the representational form for consumer heterogeneity has a substantial impact on the design and profitability of the resulting optimal product line — even for the design of a single product. The method is managerially valuable because it yields product line solutions efficiently, accounting for marketing-based preference heterogeneity as well as engineering-based constraints with which product attributes can be realized.

A ReliefF attribute weighting and X-means clustering methodology for top-down product family optimization

This article proposes a top-down product family design methodology that enables product design engineers to identify the optimal number of product architectures directly from the customer preference data set by employing data mining attribute weighting and clustering techniques. The methodology also presents an efficient component sharing strategy to aid in product family commonality decisions. Two key data mining models are presented in this work to help guide the product design process: (1) the ReliefF attribute weighting technique that identifies and ranks product attributes, and (2) the X-means clustering approach that autonomously identifies the optimal number of candidate products. Product family commonality decisions are guided by once again employing the X-means clustering technique, this time to identify the components across product families that are most similar. A family of prototype aerodynamic air particle separators is used to evaluate the efficiency and validity of the proposed product family design methodology.