Capacity Planning Method Research Articles

Analisis Kapasitas Produksi Menggunakan Metode Rough Cut Capacity Planning Pada CV Tahaki Multi Kreasi

CV Tahaki Multi Kreasi is a company engaged in interior, exterior and advertising. The number of requests for cabinet room products tends to fluctuate every month. In 2023, from January to December, CV Tahaki Multi Kreasi received 143 cabinet room order projects. To estimate the amount of demand, effective forecasting is needed. Forecasting uses methods namely Moving Average, Exponential Smoothing, and Trend Analysis. The most effective forecasting uses the Trend Analysis method which has the smallest forecasting error. The MAD value is 1.9005, MSE is 4.5343, and MAPE is 19.2362. The production schedule at CV Tahaki Multi Kreasi is carried out every two weeks for optimal results. Production capacity requirements are calculated using the Rough Cut Capacity Planning (RCCP) method. The RCCP method is used to determine the possibility of insufficient capacity or overload in determining production capacity.. The total capacity required in all work centers is 962 hours, while the total available capacity is 2016 hours. The analysis shows that there is no capacity shortage at each work station because the variance shows negative and the load percentage is 54.2%.

Entropy weight based optimal capacity planning and evaluation method of wind-photovoltaic-ESS combined generation system

Entropy weight based optimal capacity planning and evaluation method of wind-photovoltaic-ESS combined generation system

Research on the application and benefit of energy storage technology

The randomness, volatility and un-dispatch ability of large-scale new energy connected to the grid have caused a series of problems with the stable operation of the grid and great difficulties with power dispatch. The configuration of the energy storage power station and substation is studied through the metering and reliable capacity planning method of energy storage power station and substation capacity planning. This will improve the level of utilization of grid assets and promote the coordinated development of new energy, energy storage and the grid.

Guest Editorial: Enhancing hosting capability for renewable energy generation in active distribution networks

Guest Editorial: Enhancing hosting capability for renewable energy generation in active distribution networks

ANALISIS KAPASITAS PRODUKSI PADA LINI PRODUKSI BARU FORD P702 HVPO DENGAN PENDEKATAN METODE ROUGH CUT CAPACITY PLANNING (STUDI KASUS DI PT CSB)

ABSTRACTThis research is to analyze capacity requirements and availability on the production line. This research in PT CSB project FORD P702 HVPO production line. Data analysis used the Rough Cut Capacity Planning (RCCP) method by measuring work (time study), forecasting, aggregate planning, master production schedule and capacity analysis with RCCP.Based on research, standard time is 745 seconds / unit for new prodject FORD P702 HVPO. The best forecasting method is use Single Moving Average with an MAD error value of 0.04 and MSE error value of 0.021. Aggregate planning calculation results is 27144 units per year with cost of Rp 49,563,348 per year. And the conclusion is the capacity of the FORD P702 HVPO production line is sufficient and feasible to meet customer needs. This research is calculated based on the total production capacity of 19,958,400 seconds per unit in 1 year and the total required capacity of 18,618,775 seconds per unit in 1 year.

Analysis of production capacity planning to meet the consumer request using the Rough Cut Capacity Planning (RCCP) method in PT. Maccon Generasi Mandiri Makassar, Indonesia

Analysis of production capacity planning to meet the consumer request using the Rough Cut Capacity Planning (RCCP) method in PT. Maccon Generasi Mandiri Makassar, Indonesia

Analysis of production capacity planning to meet the consumer request using the Rough Cut Capacity Planning (RCCP) method in PT. Maccon Generasi Mandiri Makassar, Indonesia

Maccon Generasi Mandiri Makassar company is one of a manufacturing company engaged in the production of light brick AAC (Autoclaved Aerated Concrete). PT. Maccon Generasi Mandiri Makassar has a production capacity of 15024 〖 m〗^3 in a month or 180288 〖 m〗^3 in a year. However, with this capacity, the company is often unable to meet high consumer demand of 181450 〖 m〗^3 in a year due to less than optimal engine performance, a number of hours of work and an unbalanced workforce in the producing light brick of ACC (Autoclaved Aerated Concrete). This requires the company to plan the optimal production of capacity in order to fulfill the consumer demand in a timely and appropriate amount so that the expected of company profits will be increased. The purpose of this research is to plan production capacity in the future based on the demand rate of the consumer using the Rough Cut Capacity Planning (RCCP) with the method is Bill of Labor Approach (BOLA) technique. Based on the data processing which has been done, the recommended made were a combination of engine additions and working time. This is realized to fulfill the lack of production capacity. For the January Period = 19872 hours/month, February = 19008 hours/month, March = 19872 hours/month, April = 19008 hours/month, May = 18144 hours/month, June = 18144 hours/month, July = 19872 hour/month, August = 18144 hours/month, September = 17280 hours/month, October = 18144 hours/month, November = 18144 hours/month, December = 17280 hours/month.

Research on Site Selection and Capacity Determination of Mobile Energy Storage in Extreme Scenarios Considering the Behaviour of Decision

In order to ensure that the power supply can be restored quickly and efficiently under extreme conditions, an evaluation and decision-making method for mobile energy storage site selection and capacity planning considering the behaviour of decision makers is proposed. The prospect value is calculated based on the prospect theory to describe the bounded rationality and loss aversion of decision makers, and the attribute weight is calculated based on the relative closeness, and then the comprehensive value is obtained. Based on this, we can choose a mobile energy storage installation plan that is more in line with the psychology of decision makers.

EVALUASI KAPASITAS PRODUKSI BAN MENGGUNAKAN METODE RCCP DENGAN PENDEKATAN BOLA

Capacity planning in a company's production process needs to be considered so that the products produced meet consumer demand. PT X, is a manufacturing company that focuses on tire production. One type of large-sized tire product that has the highest demand is the ABC type with a sTabel production amount per month and demand that goes up every year. In terms of fulfilling customer demand, especially requests for large tires with type ABC, PT X often has difficulty in meeting consumer demand, this happens because the capacity of the machine is not available. Therefore, the existing production capacity must be evaluated to find out whether the available capacity is sufficient with the required capacity. To analyze this problem, the Rough Cut Capacity Planning (RCCP) method, this method is to analyze and test the determination of capacity in the master production schedule. Calculation of available capacity and capacity required in a year is carried out for the process carried out, namely: Building, Spreading and venting, curing, and Trimming. For the building and trimming process, it is found that the decision of the acupacity is fulfilled, while the Spreading and venting process is required to add 1 machine, and the curing process is required to add the machine according to the number of requests per month. From these results it can be given a proposal that needs to be considered in meeting the capacity to meet consumer needs while still paying attention to production costs.

Indoor Omnidirectional Antenna Network Planning using Capacity and Coverage Planning in Gandaria 8 Office Tower Building in PT Artisan Wahyu

Planning to improve the signal condition of cellular telephone networks in a company is very important. PT. Artisan Wahyu is a company engaged in property and real estate. The purpose of this study was to determine the quality and strength of the signal beam at the Gandaria 8 Office Tower using the G-net Track Lite application, to determine the number of indoor omnidirectional antennas based on capacity planning method, and for determining the number of omnidirectional indoor antennas based on coverage planning method. The research method used is quantitative method with a descriptive type of research. By using the analysis method of Capacity Planning and Coverage Planning. Therefore, it is necessary to plan an omnidirectional indoor antenna analysis so that activities in communication can be enjoyed properly. From the results of the research conducted, there were four plans for omnidirectional indoor antenna networks for the 2nd floor based on capacity and coverage of 6 antennas. Whereas for the 22nd floor based on capacity as much as 3 and for coverage as many as five antennas so that the Coverage Planning method is recommended to be applied to the Gandaria Building 8 Office Tower. (FF, FA, RM)

Capacity Planning of Distributed Wind Power Based on a Variable-Structure Copula Involving Energy Storage Systems

Distributed wind power (DWP) needs to be consumed locally under a 110 kV network without reverse power flow in China. To maximize the use of DWP, this paper proposes a novel method for capacity planning of DWP with participation of the energy storage system (ESS) in multiple scenarios by means of a variable-structure copula and optimization theory. First, wind power and local load are predicted at the planning stage by an autoregressive moving average (ARMA) model, then, variable-structure copula models are established based on different time segment strategies to depict the correlation of DWP and load, and the joint typical scenarios of DWP and load are generated by clustering, and a capacity planning model of DWP is proposed considering investment and operation cost, and environmental benefit and line loss cost under typical scenario conditions. Moreover, a collaborative capacity planning model for DWP and ESS is prospectively proposed. Based on the modified IEEE-33 bus system, the results of the case study show that the DWP capacity result is more reasonable after considering the correlation of wind and load by using a variable-structure copula. With consideration of the collaborative planning of DWP and load, the consumption of DWP is further improved, the annual cost of the system is more economical, and the quality of voltage is effectively improved. The study results validate the proposed method and provide effective reference for the planning strategy of DWP.

Implementation of The Rought Cut Capacity Planning (RCCP) Methods for The Planning of Bottled Drinking Water Production Capacity: A study case

Syifa Ltd is a manufacturing company that produces bottled drinking water with several types of products produced from their production floor. The main objective of this research was to predict the total quantity production of the 220 ml bottled mineral water to meet the consumer demand as scheduled time. In forecasting the demand for production of the 220 ml glass bottle packaging, the methods used were the Weighted Moving Average (WMA) method and the Single Exponential Smoothing (SES) method by comparing the size of forecasting errors using Mean Absolute Deviation (MAD), Mean Square Error (MSE), and Mean Absolute Percentage Error (MAPE). To determine the supply of glass bottles used the EOQ (Economy Order Quantity) method to determine the purchase of the most economical glass bottles. The Rought Cut Capacity Planning (RCCP) analysis result shows that there was insufficient capacity/lack of capacity in the filling and packing work center. Alternative capacity management used to optimize production utility to 95% and make capacity adjustments (re-adjustment). So that alternative capacity management was able to meet the capacity shortages that occur

Bi‐level optimal planning model of power flow router based on convex relaxation optimisation and sensitivity analysis method

To improve the utilisation of renewable energy and the power transmission capacity in the power system, the concept of power flow router (PFR) is proposed by scholars worldwide. However, there lacks an optimal planning method for PFR based on the economic principle, which impedes the development of PFR. To solve the above problem, the optimal location and capacity planning method of PFR is researched in this study, where a bi-level algorithm based on the convex relaxation optimisation and sensitivity analysis method is proposed. First, the definition and the general power flow model of PFR are introduced. According to the principle of engineering economy, the allocation model of PFR is established by introducing the binary variables. To solve the non-linear and non-convex mixed-integer programming problem, this study proposes a bi-level algorithm with the convex relaxation optimisation and sensitivity analysis method. Finally, the case studies are conducted in IEEE 30, IEEE 57 and IEEE 118 systems. The calculation results of the optimal power flow, planning results and economical analysis of PFRs are verified in IEEE 30, 57 and 118 systems, which shows the accuracy of the proposed algorithm.

Energy storage locating and sizing method in grid-connected micro-grid

In micro grid, the distributed generations have a large proportion and the energy storage system is the fundamental structure of the micro grid. Wind and photovoltaic power generation contain intermittent and uncertain characteristics. Energy storage system in micro grid can smooth the volatility of distributed power and supply power to important loads in case of the insufficiency of distributed power generation. In this paper, a location and capacity planning method of energy storage system is proposed. The energy storage installation points are the key points of the system, which are identified based on the electrical distance. Further, the capacity is optimized and solved on these basics. Finally, the effectiveness of the proposed method is verified through case studies.

Deep-Learning-Based Joint Optimization of Renewable Energy Storage and Routing in Vehicular Energy Network

Recent development in renewable energy-enabled electric vehicles (EVs) has posed challenges to the stability and efficiency of the vehicular energy network (VEN), which is a concrete implementation of Internet of Things (IoT) in energy and vehicular networks. In this article, we study a VEN with time-varying point-to-point traffic flow and adjustable energy storage capacity at stations. The goal is to jointly optimize the routing and dynamic storage allocation of renewable energy so as to maximize the efficiency of plant-to-station energy transferring. We first adopt a time-expanded topology graph to describe the scenario and model it as a maximum flow problem. Next, we incorporate routing in our methodology and derive a joint energy storage capacity and route planning method based on linear programming. Then, the problem is extended to a more general case, where the traffic pattern of the VEN is unknown. We apply the long short-term memory model, a deep learning method, to predict the traffic pattern and utilize the concept of reinforcement learning to iteratively improve the prediction accuracy. To evaluate the performance, we implement our method first on regular buses, then extend to EVs based on the real trace data from the PeMS system in California. The simulation results show that the joint optimization can achieve near-optimal performance and performs well even in case of high rate of missing traffic information, with the help of deep reinforcement learning.

Production Capacity Optimization with Rough Cut Capacity Planning (RCCP)

One of the factors supporting the company’s success in achieving its goals is the ability to meet demand and provide satisfaction to customers. A musical instrument industry makes products with a make to order system, so that it requires the accuracy and smoothness of the production process to meet the demand in accordance with the specified time. Based on data on average total daily production of Spray and Sanding Balikan Factory 2, it known that there is still often an imbalance between the actual productions of the planned production at regular work time. This study aims to analyse and evaluate the capacity of production resources and facilities. The Rough Cut Capacity Planning (RCPP) method is a method that can show a comparison between the actual capacity available and the capacity needed. Based on the research results, workload rearrangement must be carried out to distribute labor and increase work hours 90 minutes and 120 minutes so that demand can be fulfilled.

Integrated Scheduling and Capacity Planning with Considerations for Patients' Length-of-Stays.

Motivated by the shortcoming of current hospital scheduling and capacity planning methods which often model different units in isolation, we introduce the first dynamic multi-day scheduling model that integrates information about capacity usage at more than one location in a hospital. In particular, we analyze the first dynamic model that accounts for patients' length-of-stay and downstream census in scheduling decisions. Via a simple and innovative variable transformation, we show that the optimal number of patients to be allowed in the system is increasing in the state of the system and in the downstream capacity. Moreover, the total system cost exhibits decreasing marginal returns as the capacity increases at any location independently of another location. Through numerical experiments on realistic data, we show that there is substantial value in making integrated scheduling decisions. In contrast, localized decision rules that only focus on a single location of a hospital can result in up to 60% higher expenses.

A Systematic Mapping Study of Cloud Resources Management and Scalability in Brokering, Scheduling, Capacity Planning and Elasticity

Cloud computing allows for resource management through various means. Some of these include brokering, scheduling, elasticity and capacity planning and these processes helps in facilitating service utilization. Determining a particular research area especially in terms of resources management and scalability in the cloud is usually a cumbersome process for a researcher, hence the need for reviews and paper surveys in identifying potential research gaps. The objective of this work was to carry out a systematic mapping study of resources management and scalability in the cloud. A systematic mapping study offers a summarized overview of studies that have been carried out in a particular area of interest. It then presents the results of such overviews graphically using a map. Although, the systematic mapping process requires less effort, the results are more coarse-grained. In this study, analysis of publications were done based on their topics, research type and contribution facets. These publications were on research works which focused on resource management, scheduling, capacity planning, scalability and elasticity. This study classified publications into research facets viz., evaluation, validation, solution, philosophical, option and experience and contribution facets based on metrics, tools, processes, models and methods used. Obtained results showed that 31.3% of the considered publications focused on evaluation based research, 19.85% on validation and 32% on processes. About 2.4% focused on metric for capacity planning, 5.6% focused on tools relating to resource management, while 5.6 and 8% of the publications were on model for capacity planning and scheduling method, respectively. Research works focusing on validating capacity planning and elasticity were the least at 2.29 and 0.76%, respectively. This study clearly identified gaps in the field of resources management and scalability in the cloud which should stimulate interest for further studies by both researchers and industry practitioners.

Investigation on Statistical Sizing Schemes for Hybrid Energy Storage Systems

This paper explores the power and capacity planning problems in hybrid energy storage systems (HESS) used in grid-connected solar/wind power systems using statistical analysis and numerical methods. A proper HESS operation and power management system allows for real-time power distribution control with the required system dynamic response and the characteristics of the internal energy storage devices. The goal of instantaneous power allocation of HESS is to effectively manage the state of charge (SOC), power level, and operating conditions of its internal energy storage devices to achieve optimal efficiency and capacity optimisation. The HESS power and capacity planning method discussed in this paper can be used in most HESS planning cases on a given set of system operating conditions. In order to present the feasibility of the proposed method, the HESS application case discussed in this paper aims to smooth the power fluctuation of wind and solar power generations and simultaneously ensure the specified dispatching power level and quality. In this paper, HESS cases analysis and numerical comparison studies are carried out with a typical solar/wind power generation system corresponding to two different power dispatching levels.

ANALISA PERENCANAAN KAPASITAS PRODUKSI PADA PT. MUNCUL ABADI DENGAN METODE ROUGH CUT CAPACITY PLANNING

Production capacity planning this company have obstacle in meeting its production target, then company oftentimes unable to fulfill consumer demands. It can be inflict the company loose. The problems is how planning production capacity based on Rough Cut Capacity Planning (RCCP) Method in order to make consumers demand be able to supplied? “ The researcher attempt to resolving problem in PT Muncul Abadi by aiming calculate product capacity plan based on Rough Cut Capacity Planning Method and determine required product. To be useful as consideration for the company in planning production. Forecast done within the coming one year term. Capacity planning base on Rough Cut Capacity Planning (RCCP) Method. From forecast result toward previous demand quantity period within 12 periods we could be make production index schedule and order Bill of Resources with standard time that is 0,000316 hours/kg. Able to know machine capacity need in 1 workday = 8 hours day, with 3 shifts per day, 1 week = 6 workdays, 1 month = 25 effective workdays then : available time per month = 25 effective workdays x 8 hours day x 3 shift per day = 600 hours/month. Available capacity for Washing machine = 1.394 hours/month. Available capacity for Crushing machine = 1.394 hours/month. Available capacity for Pelletizing machine = 1.859 hours/month.