Optimal Total Cost Research Articles

Homogeneous reactive distillation: The influence of pressure drop on separation and reaction kinetics

This study investigates the Total Annual Cost (TAC) optimization of a reactive distillation (RD) process for methyl acetate (MA) production as a function of tray pressure drop, focusing on the trade-off between chemical reaction kinetics and separation efficiency. The analysis examines how variations in column diameter and weir height influence the TAC across different liquid hold-ups with and without incorporating a tray pressure drop in the simulations. Results indicate that for larger liquid hold-ups, the decrease in separation efficiency predominates over kinetic advantages, leading to higher energy costs when pressure drop is considered. Despite the loss in separation efficiency with a high weir height, a pressure drop-incorporated column design featuring a high weir height and small diameter is shown to achieve lower TAC due to the comparatively lower installed costs. A reduction of tray liquid hold-up of more than 50 % is found for the optimal column design in the considered case study when the tray pressure drop is considered. A sensitivity analysis towards a hypothetical infinite fast reaction is conducted to illustrate how the energy costs are affected by the kinetic rate of the chemical reaction.

Efficient neural network-aided seismic life-cycle cost optimization of steel moment frames

In this paper, a novel and efficient neural network-based methodology is proposed to achieve seismic total cost optimization of steel moment-resisting frames in a timely manner. The computational burden of an optimization process based on performing nonlinear time-history analysis is prohibitively high. To address this crucial issue, a new and efficient neural network model is proposed in this paper to accurately predict the nonlinear time history response of steel frames during the optimization process. In the proposed neural network model, an ensemble of parallel neural networks is used to provide excellent prediction accuracy. In addition, a new repairability constraint is proposed to check the seismic damage level of structures during the optimization process with the aid of the proposed neural network model. Moreover, an efficient metaheuristic algorithm is used to achieve the optimization task. Two numerical examples are illustrated to demonstrate the efficiency of the proposed methodology. The results show that the proposed neural network model outperforms the existing standard models in terms of prediction accuracy. Furthermore, it is shown that by using the proposed methodology, the optimal seismic total cost of steel frames increases by less than 2.5%, yet their seismic collapse capacity increases by at least 30%.

Multi-objective optimization of a hydrogen production process for polymer membrane coupled with electrochemical hydrogen pump from hydrogen-doped natural gas by NSGA-II

In this work, a novel process of polymer membrane coupled with electrochemical hydrogen pump (EHP) was proposed to achieve efficient hydrogen production from hydrogen-doped natural gas (HDNG), and was simulated by UniSim Design. A hydrogen separation unit of two-stage polymer membrane was used for achieving hydrogen enrichment from low H2 concentration HDNG. Due to the hydrogen upgrade, EHP was operated at a H2 concentration much higher than HDNG, resulting in low energy consumption. Benefiting from the synergy between hydrogen upgrade and purification, the coupling process brought substantial effect while improving the hydrogen purity and recovery rate and reducing the hydrogen separation cost. The real natural gas components were considered into HDNG to ensure the effectiveness of process simulation. An optimization strategy considering both product yield and production cost was proposed to achieve the trade-off between hydrogen recovery rate and separation cost. However, the impact of process parameters on the objectives is nonlinear and difficult to describe with mathematical expressions. Therefore, an agent model of the proposed process was established based on back propagation neural network (BPNN), and multi-objective optimization of H2 recovery rate and total annual cost (TAC) of hydrogen separation unit was achieved using non-dominated sorting genetic algorithm-II (NSGA-II). Investigations with HDNG under various operating conditions (feed pressure of 8–40 bar and feed H2 concentration of 5–25 mol%) were performed, which proved that 90 % overall H2 recovery rate and 99.99 mol% H2 purity of hydrogen product can be achieved at low cost, with the lowest hydrogen separation cost of 1.00 $/kg H2 achievable at 40 bar feed pressure and 25 mol% feed H2 concentration. In summary, this coupling process can provide engineering solutions for efficient hydrogen production from HDNG and promote the development of green hydrogen.

Three warehouse inventory model for non-instantaneous deteriorating items with quadratic demand, time-varying holding costs and backlogging over finite time horizon

This paper presents a novel sustainable inventory model tailored for non-instantaneous deteriorating items, incorporating quadratic demand and time-dependent holding costs. Notably, the model accounts for shortages over a finite time horizon, simulating real-world scenarios. The inventory management the strategy involves distributing products across three warehouses: the Own Warehouse (OW) and two Rental Warehouses (RW), with applications spanning supermarkets, bakeries, malls, and floral businesses. The primary objective is minimizing total costs to enhance consumer satisfaction and bolster profits. The theoretical framework is substantiated through numerical examples, focusing on the critical finding regarding optimal total cost. A special methodology is employed to balance inventory dynamics amidst various warehouses, optimizing resource allocation and mitigating shortages. Furthermore, a comprehensive sensitivity analysis using MATLAB Software unveils the repercussions of parameter modifications, providing valuable insights for decision-makers in diverse industrial settings.

Perencanaan Perawatan Mesin Building Dengan Metode Reliability Centered Maintenance (RCM)

PT. Bridgestone Tire Indonesia is a tire manufacturing company. Machines that work continuously and lack of stock availability of machine spare parts cause damage and increase maintenance costs. To reduce the occurrence of damage and increase maintenance costs, it is necessary to have an optimal maintenance policy so that the machine can operate well. To overcome the problems in this research using the Reliability Centered Maintenance (RCM) method, the first step is determining the critical components on the machine, preparing the FMEA table based on the function data of the components and maintenance reports and calculating the Risk Priority Number (RPN), then calculating the MTTF and MTTR to determine maintenance and repair intervals and find optimal total maintenance costs. Machine building has the highest frequency of downtime so this research will focus on machine building components. The results of data processing show that the highest frequency of machine damage and total downtime is the cause of hose component failure due to poor hose quality and seal components becoming worn, causing increased frequency of damage, downtime and maintenance costs. Based on maintenance cost calculations using the RCM method, hose and seal components experienced a decrease in costs, namely hose components by 55.13% and seal components by 25.45%. The proposed building machine maintenance for hose and seal components in particular is to carry out scheduled tasks, scheduled exhaust tasks, and default actions with the task category of finding failures and results for maintenance time intervals for hose components of 280.81 hours and for seal components of 134.08 hours.

Multi-Objective Optimal Scheduling of Microgrids Based on Improved Particle Swarm Algorithm

Microgrid optimization scheduling, as a crucial part of smart grid optimization, plays a significant role in reducing energy consumption and environmental pollution. The development goals of microgrids not only aim to meet the basic demands of electricity supply but also to enhance economic benefits and environmental protection. In this regard, a multi-objective optimization scheduling model for microgrids in grid-connected mode is proposed, which comprehensively considers the operational costs and environmental protection costs of microgrid systems. This model also incorporates improvements to the traditional particle swarm optimization (PSO) algorithm by considering inertia factors and particle adaptive mutation, and it utilizes the improved algorithm to solve the optimization model. Simulation results demonstrate that this model can effectively reduce electricity costs for users and environmental pollution, promoting the optimized operation of microgrids and verifying the superior performance of the improved PSO algorithm. After algorithmic improvements, the optimal total cost achieved was CNY 836.23, representing a decrease from the pre-improvement optimal value of CNY 850.

Optimal sizing and operation of electrochemical hydrogen compression

Hydrogen compression is necessary for efficient hydrogen storage, transportation, and in high-pressure chemical processes. A promising alternative to traditional mechanical compressors is electrochemical compression. As a novel technology, there are still open questions regarding the optimal design and operation in terms of total cost and the influence of the pressure level on the optimal operating point. We analyze the efficiency and economic performance of such compression. We develop a dynamic and spatially distributed (1D) model of an electrochemical hydrogen compressor. We investigate hydrogen compression at low to high pressure levels. Moreover, an operational and capital cost analysis is performed, and the optimal current density and temperature are determined. The results reveal that lower temperatures, and higher current densities tend to be favorable at higher target pressures. The optimal total cost for the considered compressor varies from 0.6 ▪ to 2 ▪ for compression to 1 MPa and 70 MPa, respectively.

Optimal scheduling of integrated energy system using decoupled distributed CSO with opposition-based learning and neighborhood re-dispatch strategy

Integrated energy optimization scheduling (IEOS) is a complex problem aiming to minimize the total cost while the requirements of load balance is met. Due to the non-convex, non-differentiable and high-dimensional characteristics, there are many difficulties in solving the problem. Based on a regional integrated energy system (RIES), a decoupled distributed crisscross optimization with opposition-based learning and neighborhood re-dispatch strategy (DDCSO-OBL-NR) is proposed to solve IEOS problem by distributed method with different energy types as the scale. Initially, the CSO with excellent global search ability is firstly used to solve the complicated IEOS problem. Then, based on the distributed structure, distributed parallel computing can be achieved by DDCSO, which contributes to 1) protect the privacy of different energy data, 2) reduce the solving dimensions and 3) relieve the heavy communication burden. The total optimal cost is achieved by minimizing the cost of each portion without centralized controller. Furthermore, the opposition-based learning (OBL) strategy and the neighborhood re-dispatch (NR) strategy are combined into DDCSO aiming to optimize initial population location and enhance local search ability. Eventually, the DDCSO-OBL-NR is realized, and the effectiveness of which in solving the distributed IEOS problems is verified by the experimental results of three cases.

Analisis Ketersediaan Kedelai Pada Koperasi Karya Mulya desa Sepande Kabupaten Sidoarjo

Karya Mulya Cooperative is a cooperative that provides soybean raw materials for tofu and tempeh craftspeople in Sepande Village, Sidoarjo Regency. This study aims to determine the optimal amount of soybean raw material inventory that should be carried out by Koperasi Karya Mulya, the optimal frequency of purchasing raw materials, the right time to purchase raw materials, the optimal total ordering cost made for the procurement of soybean raw materials, and the implementation of an effective and efficient warehouse management system. This type of research is descriptive quantitative by describing the control of raw material inventory carried out by cooperatives through data obtained and then analyzed. Data analysis used includes Economic Order Quantity (EOQ), Reorder Point (ROP), Safety Stock (SS), and FIFO methods. Based on the results of the analysis using the EOQ method, Koperasi Karya Mulya should order an optimal raw material frequency of 6,459.14 tons with a purchase frequency of 210 times, ROP 7.009,25 tons, Safety Stock of 5.857,81 tons and total storage costs of Rp427,272,734.03.

Inventory Control for Eyeglass Supply Using the P Model Based on Sales Products Sales Forecasting (Case Study: Merry Optic Bandung)

Inventory is a resource owned by the company to be used in the production process to meet consumer demand. Companies must be able to control inventory appropriately in order to avoid excess or shortage of inventory by using inventory control. Inventory control is a necessary part of a company that requires an appropriate inventory policy to meet uncertain needs. Based on this background, this study discusses the single item inventory model in the form of photochromic glasses at Merry Optik to find the optimal total inventory cost. In meeting the uncertain needs of the company, the Additive Decomposition forecasting method is used in order to find out the forecast sales data pattern in the future. Uncertain demand causes the inventory system to be probabilistic, so it is necessary to carry out probabilistic inventory control. The P model of the case of back orders was chosen because the range of ordering periods is fixed and the company can buy inventory when it runs out before the time the inventory order is made so that buyers can wait until the inventory arrives. By using Model P for the case of back orders, the company can obtain the period between orders, the total cost of inventory, and the optimal level of service. Based on the results of this study, a pattern of sales forecast data is obtained which repeats every 12 months. Companies must order glasses within a period of 32 days between orders so that it is optimal and able to provide a reduction in the total inventory cost of IDR 21,828,771 with a service level of 95%. Companies can save on inventory costs if they use shorter periods between orders. The total cost of inventory can be more optimal if the company reduces the cost of storing inventory in the warehouse.

Inventory Control for Eyeglass Supply Using the P Model Based on Sales Products Sales Forecasting (Case Study: Merry Optic Bandung)

Inventory is a resource owned by the company to be used in the production process to meet consumer demand. Companies must be able to control inventory appropriately in order to avoid excess or shortage of inventory by using inventory control. Inventory control is a necessary part of a company that requires an appropriate inventory policy to meet uncertain needs. Based on this background, this study discusses the single item inventory model in the form of photochromic glasses at Merry Optik to find the optimal total inventory cost. In meeting the uncertain needs of the company, the Additive Decomposition forecasting method is used in order to find out the forecast sales data pattern in the future. Uncertain demand causes the inventory system to be probabilistic, so it is necessary to carry out probabilistic inventory control. The P model of the case of back orders was chosen because the range of ordering periods is fixed and the company can buy inventory when it runs out before the time the inventory order is made so that buyers can wait until the inventory arrives. By using Model P for the case of back orders, the company can obtain the period between orders, the total cost of inventory, and the optimal level of service. Based on the results of this study, a pattern of sales forecast data is obtained which repeats every 12 months. Companies must order glasses within a period of 32 days between orders so that it is optimal and able to provide a reduction in the total inventory cost of IDR 21,828,771 with a service level of 95%. Companies can save on inventory costs if they use shorter periods between orders. The total cost of inventory can be more optimal if the company reduces the cost of storing inventory in the warehouse.

Modeling of Junior Servers Approaching a Senior Server in the Retrial Queuing-Inventory System

This article deals with the queuing-inventory system, composed of c junior servers, a senior server, two finite waiting halls, and an infinite orbit. On occasion, junior servers encounter challenges during customer service. In these instances, they approach the senior server for guidance in resolving the issue. Suppose the senior server is engaged with another junior server. The approaching junior servers await their turn in a finite waiting area with a capacity of c for consultation. Concerning this, we study the performance of junior servers approaching the senior server in the retrial queuing-inventory model with the two finite waiting halls dedicated to the primary customers and the junior servers for consultation. We formulate a level-dependent QBD process and solve its steady-state probability vector using Neuts and Rao’s truncation method. The stability condition of the system is derived and the R matrix is computed. The optimum total cost has been obtained, and the sensitivity analyses, which include the expected total cost, the waiting time of customers in the waiting hall and orbit, the number of busy servers, and a fraction of the successful retrial rate of the model, are computed numerically.

ANALISIS PENGENDALIAN KUALITAS PRODUK PADA KONVEKSI NITRA JAYA DI KABUPATEN BADUNG

Declining product quality often occurs during the production process which can affect product quality. Damaged products can be done by the company by controlling the quality of the products produced through many methods such as DMAIC (Define, Measure, Analyze, Improve and Control), Six Sigma and Statistical Quality Control (SQC). This research was conducted at the Nitra Jaya Convection which is located on Jalan Raya Panglan, Banjar Cepaka Kapal, Mengwi District, Badung Regency, Bali. The data analysis technique used is statistical quality control (SQC) by using tools such as check sheets, P-charts, Fishbone diagrams and Quality Costs. The results of the analysis of the cost of production quality at the Nitra Jaya Convection for the 2019 period still show that the actual quality costs incurred by the company are still greater than the optimal quality costs that should be incurred by the company. The actual damage was 116 pcs of uniforms, with a total cost of quality (TQC) of Rp13.244.958. The lowest point or the optimal point of quality costs is at the damage limit of 195 pcs of uniforms with an optimum total cost of quality (TQC) of Rp11.647.055. This shows that quality control has not been implemented optimally.

Project Acceleration By Time and Cost Optimization at PT. Dui Esa Unggul With CPM & Pert Method

Projects are activities that are temporary in nature, have deadlines, budgets, resources and have product specifications to be produced. The case study of this research is the Matarbari Throat Ring Unit-2 fabrication project carried out by PT. Dui Esa Superior . The purpose of this study is to determine the factors that cause project delays, and to find out how long the duration and the optimal cost for the project are. The methods used are FTA (Fault Tree Analysis), CPM (Critical Path Method), and PERT (Project Evaluation and Review Technique). The results of direct field observations and interviews, as well as analysis and evaluation using the FTA, CPM and PERT methods, obtained 19 basic event factors causing project delays, namely labor shortages, workers lack of understanding of drawings, bad weather / rain , and others. There are 9 basic event combinations or minimum cut sets, namely (D1*D2*D3), (D4*D5), (C3), (D6), (E1*E2), (E3*E4*E5), (F1 ), (F2*F3*F4), (F5*G1*G2). The optimal duration of the Matarbari Throat Ring Unit-2 project is 57 days from the normal 61 days with a 69.15% chance. The total optimal cost of the Matarbari Throat Ring Unit-2 project with the optimal duration is Rp. 127,772,400.

A Study on Two-Warehouse Inventory Systems with Integrated Multi-Purpose Production Unit and Partitioned Rental Warehouse

A study of two warehouse inventory systems with a production unit is developed in this article with some constraints which are of practical applicability to optimize the total production cycle and its cost. A production unit evolves in three different states to retain its quality and prolong its lifetime: the state of producing items, the state of reworking the identified defective items, and the state of being idle. It processes the items up to a certain time point. The screening process starts immediately after a product comes out of the production unit. The classified non-defective items are first stored in own warehouse (OW), after filling to its maximum capacity, and the remaining items fill in the first block RW1 of the rental warehouse RW. All identified defective items are stored in the second block RW2 of RW. The holding cost of an item is higher in RW than OW. All defective items are sent to the production unit for re-do processes as a single lot immediately after the stop of the production and re-do items are stored in RW1 to satisfy the demand. The items in the RW1 are of higher priority in satisfying the demands after the stop of the production unit in producing new items as to deduce the total cost. Demand is assumed as both time and advertisement dependent and is encouraged once production starts. The deterioration rate differs in both warehouses. No backlog is entertained. The study is directed to achieve optimum total cycle cost towards the attainment of the optimum production time slot and the entire cycle of the system. We have arrived at explicit expressions for the total cost function of the entire production cycle. An analytic optimization process of the discriminant method is employed in the form of an algorithm to arrive at the optimum total cost. It provides a numerical illustration of a specific environment. The implications of the current research work are as follows. The optimum utility of production units in three different states in arriving at the optimum total cost is extensively studied with respect to deterioration, demand, and production rates. It also examined the influence of fluctuating deterioration, demand, and production parameters in arriving at optimum deterioration cost, holding cost, and total cycle cost, as they have important managerial insights. The effect of rental charges on the optimum total cost is examined as the system is used for multi-purpose storage.

Application of Improving ABC in Cold Chain Low Carbon Logistics Path Planning

The market has set higher efficiency and environmental requirements for cold chain logistics, and path planning plays an important role. This study proposes a low-carbon cold chain logistics path planning model based on an improved artificial bee colony algorithm (this paragraph refers to ”fusion algorithm”). The study first establishes the fusion algorithm. Then, in response to the shortcomings of this algorithm, the artificial fish swarm algorithm and genetic algorithm are used to improve it. The final results express that the shortest distance for solving Eil51 using this algorithm is 421.38, the longest distance is 448.58, and the average distance is 439.34; The shortest distance for solving Ulysses22 is 72.46, the longest distance is 73.63, and the average distance is 72.84. The average convergence times for Eil51 and Ulysses22 are 133.57 and 7.86, and the optimal performance ratios for relative error are 0.0076 and 0.0051. The robust performance ratios are 0.0362 and 0.0117. The optimal total cost solution and the average value for solving the relevant distribution problem are 47,894.6 yuan and 48,562.7 yuan, respectively. In summary, the model proposed in the study has good application effects in cold chain low-carbon logistics path planning, and has a certain promoting effect on the development of cold chain logistics.

Thermoeconomic and environmental analyses based single objective optimization of subcooled compression-absorption cascaded refrigeration system using evolutionary techniques

ABSTRACT This article analyses a subcooled compression-absorption cascaded refrigeration system (SCRS) in comparison with a standalone compression-absorption cascaded refrigeration system (CRS) based on thermoeconomic optimization. Three different absorbent solution/solution mixture-refrigerant combinations have been tested as working pairs in vapor absorption refrigeration system (VARS), whereas four environmentally friendly refrigerants have been utilized in vapor compression refrigeration system (VCRS). The total annual cost of the system is formulated using energy, exergy, and economic performance of the system and is minimized for optimal operational parameters by implementing five recent evolutionary optimization techniques. The effect of compression subcooling on various operational parameters of the cascaded system is reported. Amid all absorbent solution/solution mixture-refrigerant-refrigerant combinations, R290 combined with (CaCl2-LiBr-LiNO3)-H2O provides the minimum total annual cost of 13,164.8 US$ yr−1 and 15,401.9 US$ yr−1 for CRS and SCRS, respectively. Sanitized Teaching Learning Based Optimization (sTLBO) and Coyote Optimization Algorithm (COA) obtain the optimal total annual cost for most VARS-VCRS absorbent solution/solution mixture-refrigerant-refrigerant combinations. Though the coefficient of performance (COP) of an optimal SCRS is about 250% higher than its optimal CRS, higher compressor work results in a higher penalty cost for the optimal SCRS, which is almost 190% higher than the optimal CRS. A quick convergence is observed for sTLBO and COA.

Analysis Of Spare Parts Inventory Planning And Control To Improve Cost Efficiency At Pt Manunggal Jaya Makmur

PT Manunggal Jaya Makmur is one of the companies engaged in the transportation and contracting-based sector that provides integrated services from the start point to the end. In addition, it is also engaged in the repair of heavy equipment such as mixer trucks, dump trucks, colt diesel, and repair of other heavy equipment. In supporting the company's activities, PT. Manunggal Jaya Makmur implements a strategy for supplying raw materials and spare parts. In its operational activities, PT. Manunggal Jaya Makmur is still constrained by the overstock problem which ultimately causes a buildup of goods. In this study, material classification was carried out using ABC Theory analysis. Then the methods used in planning and controlling inventory management are the POQ and EOQ methods. After getting the results, the methods used during the research will be compared with the methods that have been applied so far in the company to find out the most effective methods to be applied in cost efficiency and work productivity and can maximize the profits received by the company. Based on the analysis carried out, the cost of calculating the total inventory of spare parts using the EOQ method was Rp. 205,513,000, the LFL method was Rp. 274,141,349 and the POQ method was Rp. 273,502,120. So, from these data, it can be concluded that the most optimal total cost of inventory is the EOQ method to produce greater profits and minimize overstock.

Modeling and optimization of a hybrid solar-battery-diesel power system for remote consumers.

Hybrid power systems can be affected by various uncertain parameters such as technical, economic, and environmental factors. These parameters may have both positive and negative impacts on the overall performance of the system. Therefore, in this study, an effective optimization method for modeling and optimization of a hybrid solar-battery-diesel power structure for remote consumers is proposed. The purpose of this method is to find the optimal configuration of the hybrid structure from the technical-economical-environmental point of view to cover the load demand requirements of remote consumers. To verify the performance of the hybrid microgrid, the results of the hybrid system based on the hourly meteorological data and load profile are compared with the results of the conventional diesel generator (DG). The optimization problem is solved using a harmony search optimization algorithm. The results show that the solar/battery/DG system is more suitable than the DG-only system in different uncertainty indexes based on economic and environmental aspects. Also, by the increase of the uncertainty index from 0.5 to 10%, the optimal total cost of the system decreases by 36.5%, while at the same time the unavailability value increases from 0.2259% to 9.9568%. Additionally, when the interest rate value increases from 1 to 7%, the total cost value increases around 17. 4%.

Analisa Percepatan Proyek Pembuatan Mesin Grinding Cat Dengan Time Cost Trade Off Method (Studi Kasus : PT TDI Sidoarjo)

The case study in this research is a project to manufacture a paint paste grinding machine at PT Pabrik Cat Tunggal Djaja Indah. In its implementation, this project is considered to have a delay of 2 weeks, with a total project completion time of 120 days, so project acceleration is needed. The scheduling method is carried out using PDM (Precendence Diagram Method) with the help of Microsoft Project 2016 software to find the critical path, then after knowing the critical activities, crashing is carried out with the alternative of adding working hours or overtime and adding optimum workers. The Time Cost Trade Off method will analyze the time after crashing. The optimal duration to complete this project is 107 days with an acceleration of 13 working days with a percentage of 10.38% and an optimal total cost of Rp 262,947,693 with a cost efficiency of 3.56%.