Optimal Production Capacity Research Articles

Dynamic delay-based game approach in car and petrol supply chains under government intervention

Effective decision-making in a temporal context is challenged by the enduring impacts of delays, where decisions made in a certain period are influenced by choices made in preceding periods. This paper delves into the analysis of decision-making in a dynamic game system characterized by delay impact on decisions. Notably, it pioneers the application of a game approach to detect the intricate relationship between car and petrol supply chains operating under conditions of dynamism and uncertainty. The marginal profit method is applied to deal with the dynamic game model. Furthermore, this article investigates the improvement of green car levels, on member profits. In the car supply chain, the car manufacturer sells two distinct product types: green and regular. In this paper, green cars refer to cars with low petrol consumption, and as gas consumption decreases, the green level of the car ascends. This study marks the first instance where optimal production capacity allocation is examined within the framework of delay and uncertainty. Considering the government's initiative to curtail petrol consumption in automobiles, the effects of the government's supporting role are also analyzed in this paper. As a result, the greenness level witnessed a 4.1-fold increase, leading to an 81.7% surge in the demand for green cars, consequently boosting the profit of the entire car supply chain. Several numerical experiments of a real case were examined to evaluate the performance of the proposed models. Finally, some sensitivity analyses were applied to the principal parameters of the model to extract managerial insights.

Evaluation of Standard Times for Some Local Blacksmith’s Products

The practice of menial farming in the southwestern part of Nigeria have necessitated the need for the blacksmith industry to produce farm implements for the need of their immediate environment (farmers). With increased cost and time of production, coupled with demand size, reduced productivity and in order to meet the customer’s schedule, the study was conceived to evaluate the standard time to start and finish a product to manage production time and to estimate the optimum production capacity of the blacksmith workstation. After a careful survey of the local blacksmiths and with the aid of a stopwatch and study time chart, standard time was evaluated for harvester, digger and axe. These implements are the most commonly used items by the locals. The standard time for the local blacksmith’s axe, digger and harvester production was estimated to be 1458.35, 1931.44 and 936.66 Seconds respectively. It can therefore be concluded that the blacksmiths working for 8 hours a day will produce either (i) about 20 units of axe per day, (ii) 15 units of digger per day, or (iii) 31 units of harvester per day, or (iv) 7 units each, of the products per day

Generation of Monoclonal Chinese Hamster Ovary Cell Lines Using DISPENCELL-S3.

Single-cell isolation is a key step in the manufacturing of therapeutic proteins, which relies on the development of monoclonal cell lines. It increases production safety and consistency. It also ensures higher manufacturing performances thanks to the selection of the rare clonally derived cell lines with optimal growth and production capacities. DISPENCELL-S3 is a small format single-cell dispenser whose technology is based on impedance spectroscopy. Here, we provide a detailed protocol for generating Chinese hamster ovary (CHO) monoclonal cell lines using DISPENCELL-S3. Production and characterization of an adequate cell sample for single-cell isolation, as well as the optimization of the DISPENCELL-S3 dispensing parameters are described. Monoclonal outgrowth assessment and the use of the recorded impedance signal as evidence of clonality are also outlined.

Optimal production capacity matching for blockchain-enabled manufacturing collaboration with the iterative double auction method

Optimal production capacity matching for blockchain-enabled manufacturing collaboration with the iterative double auction method

Multiobjective optimization of a pressurized water reactor cogeneration plant for nuclear hydrogen production

In this paper, energy, exergy, economic analysis and multiobjective optimization of a pressurized water reactor (PWR) nuclear cogeneration plant for hydrogen production through high-temperature steam electrolysis (HTSE) are carried out. HTSE requires energy in the form of both heat and electrical work. A novel parameter, namely the heat/total energy ratio, is defined, and used as a decision variable in optimization. In addition to energy ratio, hydrogen production capacity, reactor thermal power, live steam temperature, reheating mass flow rate ratio, reheating temperature and steam extraction location are considered as the decision variables to simultaneously optimize the thermal efficiency, thermal-to-hydrogen efficiency, utilization factor, exergy efficiency and total revenue of the cogeneration plant. The analysis and optimization focus on the secondary cycle of the PWR and the effects of hydrogen and electricity prices and ambient conditions are also taken into account since these prices have a significant impact on the optimum design. For a hydrogen price of 4 $/kg and an electricity price of 0.1 $/kWh, when equal preference is given to all objective functions, the optimum production capacity is 6.778 kg/s. The energy ratio has an optimum value if the optimization focuses exclusively on the thermal efficiency and total revenue.

Optimizing Beekeeping Production through System Dynamics Modeling: A Case Study on Forecasting Bee Queen Rearing Capacity

Commercial bee queen rearing is an intensive process in which the main commercial product, bee queens, are produced in a short period of time. The intensity is even more severe in regions where the beekeeping season is shorter, as preparation, rearing initiation and capacity increase during the season consume a lot of time. Bee queens can be divided into different product categories: virgin, mated, mated in isolated station, and instrumentally inseminated queens, and they can be further divided by race, pedigree, and colony characteristics. Each category is with varying time and resource consumption. To optimize bee queen rearing and choose the appropriate rearing strategy, product categories, production capacity dynamics, and other aspects, the authors of this case study developed a system dynamics model with the aim of finding the optimal number of production units, the most appropriate product groups and their volumes, according to changes in income and time consumption. The model clearly shows the system’s sensitivity to having too many production units – nuclei and queen rearing colonies. Too many production units led to ineffective use of nuclei, increased bee queen mortality, high bee queen surplus, high human and time resource costs and unnecessary batching of orders. The developed model demonstrated how to predict the optimal production capacity and how inefficiency leads to the inevitable collapse of the bee queen rearing system, from which the bee queen breeder cannot recover during the season. The model allowed to conclude that balancing material and human resources in bee queen rearing is very important for efficient production.

PENERAPAN KAPASITAS PRODUKSI OPTIMAL UNTUK PENGUATAN USAHA PENGOLAHAN ABON IKAN DAN BAKSO IKAN DI DUSUN GILI AIR, DESA GILI INDAH, KABUPATEN LOMBOK UTARA

There are two fish processing and marketer groups in Gili Air Subvillage - Gili Indah Village. That group was formed in August 2021. Looking at the time they were created, the fish processing and marketer groups need assistance in carrying out fish processing production activities. The need for aid to the fish processing and marketer group is determining the optimal production capacity to plan processed fish production targets so that the fish processing business carried out provides maximum benefits. Assistance activities for fish processing and marketing groups in Gili Air Subvillage are carried out through educational and practical methods. Educational activities regarding setting targets for processed fish production capacity are carried out using active participatory action program methods in the field. Meanwhile, practical activities are carried out by gathering information based on participants' experiences. Based on the practice, it can be seen that the optimal production capacity carried out by the Putri Bahari group in processing fish floss is 1,200 kg per year. Meanwhile, the optimal production capacity carried out by the Lanter Gili group in processing fish balls is 920 kg per year. The results of the activities that have been carried out show that the fish processing and marketing groups in Gili Air Subvillage are willing to take advantage of the knowledge and information that has been provided in carrying out fish processing activities. This is based on the fact that the group needs to know the processing production capacity that will be produced in order to develop an appropriate strategy to generate optimal profits, there is a strategy in designing fish raw materials that need to be provided, the amount of packaging, and the division of work time.

Enumeration optimization of open pit production scheduling based on mobile capacity search domain

The optimization of open pit mine production scheduling is not only a multistage decision-making problem but also involves space–time dynamic action among multiple factors, which makes it difficult to optimize production capacity, mining sequence, mining life, and other factors simultaneously in optimizing design. In addition, the production capacity is disorderly expanded, the calculation scale is large, and the optimization time is long. Therefore, this article designs a mobile capacity search domain method to improve computing efficiency without omitting the optimal production capacity. At the same time, taking the maximum net present value as the objective function, an enumeration method is used to optimize the possible paths in different capacity domains and calculate the infrastructure investment and facility idle cost required to meet the maximum production capacity on each possible path to control the disorderly expansion and violent fluctuation of production capacity. The research shows that the open pit mine production scheduling optimization algorithm proposed in this article can not only realize the simultaneous optimization of the three elements of production capacity, mining sequence, and mining life but also improve the computing efficiency by 200 times. Furthermore, the production capacity fluctuation is less than 1.4%. The mining life of the mine is extended by 13 years, and the overall economic benefit is increased by 18%.

Responses of the tree peony (Paeonia suffruticosa, Paeoniaceae) cultivar ‘Yu Hong’ to heat stress revealed by iTRAQ-based quantitative proteomics

Horticulture productivity has been increasingly restricted by heat stress from growing global warming, making it far below the optimum production capacity. As a popular ornamental cultivar of tree peony, Paeonia suffruticosa ‘Yu Hong’ has also been suffering from heat stress not suitable for its optimal growth. To better understand the response mechanisms against heat stress of tree peony, investigations of phenotypic changes, physiological responses, and quantitative proteomics were conducted. Phenotypic and physiological changes indicated that 24 h of exposure to heat stress (40 °C) was the critical duration of heat stress in tree peony. The proteomic analyses revealed a total of 100 heat-responsive proteins (HRPs). According to bioinformatic analysis of HRPs, the heat tolerance of tree peony might be related to signal transduction, synthesis/degradation, heat kinetic proteins, antioxidants, photosynthesis, energy conversion, and metabolism. Our research will provide some new insights into the molecular mechanism under the response against the heat stress of tree peony, which will benefit the future breeding of heat-resistant ornamental plants.

ANALISIS TOKO NEW PELITA MOTOR DALAM PENGELOLAAN PERMINTAAN DAN KAPASITAS PRODUKSI DI KOTA BATAM

The economic crisis that has occurred around the world since the emergence of the Covid-19 pandemic has had a severe impact on the operational costs of a business. With that, the purpose of this research is to assist the New Pelita Motor Store in dissecting the problems that exist in them, especially in managing demand and production capacity. Data collection techniques used are literature studies and interviews with owners and employees at the New Pelita Motor Store. The interview questions discussed how their day-to-day operations were, as well as how their sales progressed from period to period. The results obtained are that the management of demand and capacity of these partners has not been effective in the operation, because New Pelita Motor Store tends to be in a manual or traditional operational position. Therefore, suggestions that can be given are to improve the consumer experience when and after receiving services and balance their demands through promotional media to get optimal production capacity.

Management and climatic pressure on the efficiency performance of snail farming in Nigeria: A trend stochastic frontier approach from 2019 – 2021

Livestock farming in Nigeria is having its share of climate variability problems which can affect its sustainability, snail is one of the livestock products that are highly susceptible to climate issues because they are subjected to several limitations like a longer period of hibernation and heat stress which increases mortality. Due to the health benefit of snail meat that has made its production very lucrative, it became necessary to conduct this study on the management and climatic pressure on the efficiency performance of snail farmers by adopting a stochastic frontier approach to operationalize the stated objectives using secondary data. The focus of the study was to establish the technical and profit efficiency of the farmers over the time trend of production. However, the study found that snail farming recorded more technical efficiency (0.940) value in 2021, whereas 2019 recorded the least technical efficiency (0.714). With this high TE record in 2021, the study caveat that farmers are producing 6% below optimal production capacity which must be closed up in a short while to stay efficient in the sector. More so, information about the profit efficiency (PE) revealed that before an average farmer attains the level of most profit-efficient snail farming, the farmer would have to up his/her profit by 25.3% (2019), 33.7% (2020), and 11.9% (2021). The study also found that the most profit-inefficient farmer would have to improve their profit by 66.8% (2019), 99.8% (2020), and 72.4% (2021) before they can come up to the most profit-efficient farmer. The study also revealed that educated farmers are more technically efficient. Interestingly, the study revealed that snail farming in the study is stock, fumigant, feed, labour, and capital dependent. The study also observed that humidity and rainfall are the climate variability that negatively affects the TE of the farmers. The study, therefore, recommends that farmers should adopt climate-friendly agriculture as a way to survive the variability that threatens food security.

Product quality optimization vs production capacity optimization: an analytical perspective

PurposeThis study aims to devise generalized unconstrained optimization models for ascertaining the optimal level of product quality and production capacity level by modeling both product price and production cost as a function of product quality. Further, interrelations among investment for quality, product quality and production volume are considered. This study contributes toward the extant research, in that nuances related to price, production volume, and product quality are fused together such that two broad operational strategies of product quality optimization and production capacity optimization can be contrasted.Design/methodology/approachTo achieve the research objectives, the authors evolve unconstrained optimization models such that optimal product quality level and optimal production capacity level can be obtained employing the principles of differential calculus aimed at maximizing the manufacturer's profit. Specifically, nuances related to quality technology and efficiency, and quality loss cost has also been integrated in the integrated model. Thereafter, employing numerical analysis for a generalized product, the detailed workings of evolved models are demonstrated. The authors further carry out the sensitivity analysis to understand the impact of investment for quality onto the manufacturer's profit for both operational strategies.FindingsThe research demonstrates that the manufacturer would be better off adopting production capacity optimization strategy as an operational policy, as opposed to product quality optimization policy for the manufacturer's profit maximization. Further, considering the two operational strategies, the manufacturer does not obtain the highest possible theoretical profit when pertinent variables (product quality and production capacity) are set at highest possible theoretical level. This research discusses that in low-volume and high-margin products, it might be useful to adopt a product quality optimization strategy as a production capacity optimization strategy results in significantly high quality loss cost.Originality/valueThe findings of our study have a significant implication for industries such as steel-making, cement production, automotive industry wherein the conventional wisdom dictates that higher level of production capacity utilization always results in higher level of revenues. However, the authors deduce that beyond certain production capacity utilization, striving for higher utilization does not fetch additional profit. This work also adds to the extant research literature, in that it integrates the nuances of product quality, production volume and pricing in an integrative manner.

OPTIMAL DECISION-MAKING IN MANUFACTURING INDUSTRY UNDER BUSINESS RISK

In the modern global economy, emerging economies have become the main source of manufactured goods to supply the advanced economies. The profits of a manufacturing firm normally increase in the amount it can produce and sell. However, in an environment of uncertainty, it is not always optimal for a manufacturing firm in emerging economies to accept big production orders even though this might mean higher revenues. This is because a corresponding higher operating leverage will necessarily increase business risk and the resulting discount rate, which may result in a lower firm value. In this study, we provide a structural framework targeting this problem where demand is stochastic, discount rate is endogenously determined based on business risk and operating leverage. We use lithium battery, an essential component in electric and hybrid cars, to demonstrate how the framework is developed and implemented. Our model helps decide the optimal production capacity as the result of the cost structure, risk aversion, and value maximization. We show how the valuation process is carried out in a theoretically consistent manner. Our framework may be extended for different sectors in emerging economies when production decisions are to be made under uncertainty.

Techno-economic assessment of the FReSMe technology for CO2 emissions mitigation and methanol production from steel plants

The iron and steel industry accounts for 6 % of the global CO2 emissions and it is one of the main hard-to-abate sectors that must be un-locked to reach climate neutrality in the coming decades. The objective of this work is to assess the economics of the FReSMe (From Residual Steel gases to Methanol) process for reducing the carbon footprint of conventional steel plants based on the Blast Furnace route. This reduction is achieved by capturing and converting part of the steel plants residual gases into methanol. The process includes the Sorption Enhanced Water Gas Shift (SEWGS) technology to treat the residual gases separating the CO2 and producing a H2-rich stream. The latter can be recirculated back to the steel plant to cover part of its primary energy demand or reacted together with part of the separated CO2 to synthetize methanol. The CO2 excess can be used for underground storage. Four different process configurations with different methanol production capacities are investigated. Costs and performances of each configuration are assessed and compared to two reference cases. Results show that the FReSMe process allows to avoid around the 60 % of the overall steel plant CO2 emissions, while the reference plant with post-combustion capture in the power section only 18 %. The cost of CO2 avoided is in the range 40.6 €/tCO2 – 46.2 €/tCO2. When no carbon tax is considered, the optimal methanol production capacity results 600 t/day with a Levelized Cost of Hot Rolled Coil of around 520 €/tHRC, 9.4 % higher than in the base case (476 €/tHRC). With a carbon tax rate above 40.6 €/tCO2, the optimal configuration has a methanol production capacity of 300 t/day and it ensures higher emissions reduction and lower costs than conventional post-combustion carbon capture systems.

Economic optima for buffers in direct reduction steelmaking under increasing shares of renewable hydrogen

While current climate targets demand substantial reductions in greenhouse gas emissions, the potentials to further reduce carbon dioxide emissions in traditional primary steel-making are limited. One possible solution that is receiving increasing attention is the direct reduction (DR) technology, operated either with renewable hydrogen (H2) from electrolysis or with conventional natural gas (NG). DR technology makes it possible to decouple steel and H2 production by temporarily using overcapacities to produce and store intermediary products during periods of low renewable electricity prices, or by switching between H2 and NG. This paper aims to explore the impact of this decoupling on overall costs and the corresponding dimensioning of production and storage capacities. An optimization model is developed to determine the least-cost operation based on perfect-foresight. This model can determine the minimum costs for optimal production and storage capacities under various assumptions considering fluctuating H2 and NG prices and increasing H2 shares. The model is applied to a case study for Germany and covers the current situation, the medium term until 2030, and the long term until 2050. Under the assumptions made, direct reduced iron (DRI) storage mainly serves as long-term storage for several weeks, similar to usual balancing storage capacities. Storing H2, on the contrary, is used for short-term fluctuations and could balance H2 demand in the hourly range until 2050. From an economic perspective, DRI production using NG tends to be cheaper than using H2 in the short term, and potential savings from the flexible operation with storages are initially small. However, in the long term until 2050, NG and H2 could achieve similar total costs if buffers are used. Otherwise, temporarily occurring electricity price spikes imply substantial increases in total costs if high shares of H2 need to be achieved.

AN ECONOMIC RESEARCH OF BROILER PROJECTS FOR SOME PROVINCES IN THE MIDDLE OF IRAQ IN 2019

This research was aimed to estimate the long-run cost and supply functions and to calculate the optimum profit-maximizing level of production, optimum capacity for broiler projects. The preliminary data were obtained by questionnaires that were distributed to project owners in Qadisiyah, Babil and Wasit governorates. A total of 80 projects amounted for 15% of the total projects in these governorates were included. The results indicated that the optimal profit-maximizing and actual production were 25,337, 34,737, and 21.25 tons respectively. The optimum production capacity was 9.9 thousand birds, while the actual capacity was 8.3 thousand chicken The cost elasticities were 0.936, 1.0 and 1.23 at the actual, optimal and profit maximizing production, respectively. The supply function had low elasticity indicating that the producers face great difficulty in controlling production in case of price changes. From these results, it can be concluded that government support is required for productive inputs, facilitating loans, preventing poultry importing, and adoption of strategic policy for the agricultural sector in general and poultry production in particular.

Optimization of thermostable proteases production under agro-wastes solid-state fermentation by a new thermophilic Mycothermus thermophilus isolated from a hydrothermal spring Hammam Debagh, Algeria

The present work investigates for the first time the presence and isolation of the thermophilic fungi from hydrothermal spring situated at the locality of Guelma, in the Northeast of Algeria. The production of the thermostable proteases and the optimization of culture conditions under agro-wastes solid-state fermentation to achieve optimal production capacity were explored. A statistical experimental approach consisting of two designs was used to determine the optimum culture conditions and to attain the greatest enzyme production. Besides, different agricultural wastes were initially evaluated as a substrate, whereby wheat bran was selected for enzyme production by the isolate under solid-state conditions. The isolate thermophilic fungi were identified as Mycothermus thermophilus by sequencing the ITS region of the rDNA (NCBI Accession No: MK770356.1). Among the various screened variables: the temperature, the inoculum size, and the moisture were proved to have the most significant effects on protease activity. Employing two-level fractional Plackett–Burman and a Box–Behnken designs statistical approach helped in identifying optimum values of screened factors and their interactions. The analysis showed up 6.17-fold improvement in the production of proteases (~1187.03 U/mL) was achieved under the optimal conditions of moisture content 47%, inoculum 5 × 105 spores/g, and temperature at 42 °C. These significant findings highlight the importance of the statistical design in isolation of Mycothermus thermophilus species from a specific location as well as identifying the optimal culture conditions for maximum yield.

A Digital Tool for Capacity Load Optimization in Spatially Distributed Production Systems

Improving the efficiency of the use of fixed assets is one of the priority tasks facing modern machine-building enterprises. It is particularly relevant for spatially distributed holding structures that have emerged in the process of reforming the domestic machine-building complex and include enterprises that produce similar products and have similar types of production assets.The purpose of the paper is to develop on the basis of mathematical modeling tools for solving problems of optimization of industrial enterprises’ fixed assets development and use.An approach to optimize the fixed assets load in a spatially distributed production system is proposed. A mathematical model in the form of a linear programming production and transport optimization problem is formulated, which allows one to find optimal production capacity load modes in a wide range of conditions. The optimal regimes of this model are studied. It is shown that in certain cases the capacity use optimization can be the only way to ensure the timely fulfillment of the customers’ ordersThe use of modern digital technologies that provide dynamic forecasting and optimization of the production capacity allows to achieve a number of improvements, including the production time and cost reduction and the growth in efficiently used production means.

On capacity reservation contract in semiconductor supply chain

This paper investigates capacity reservation and capacity preparation issue in the semiconductor industry under stochastic demand. By comparing the manufacturer's optimal production capacity preparation in vertical integrated and decentralised supply chains, it shows that the manufacturer's production capacity preparation and the market satisfaction rate of the decentralised supply chain are lower. We propose a deductible reservation (DR) contract where the retailer reserves production capacity with a fee that can be deductible from the wholesale price. In the DR contract model, channel coordination and profit split are achieved respectively by setting expanded production capacity and unit reservation fee. The DR contract provides a risk-pooling mechanism not only motivates the manufacturer to expand production capacity but also preserves the retailer's flexibility.

On capacity reservation contract in semiconductor supply chain

This paper investigates capacity reservation and capacity preparation issue in the semiconductor industry under stochastic demand. By comparing the manufacturer's optimal production capacity preparation in vertical integrated and decentralised supply chains, it shows that the manufacturer's production capacity preparation and the market satisfaction rate of the decentralised supply chain are lower. We propose a deductible reservation (DR) contract where the retailer reserves production capacity with a fee that can be deductible from the wholesale price. In the DR contract model, channel coordination and profit split are achieved respectively by setting expanded production capacity and unit reservation fee. The DR contract provides a risk-pooling mechanism not only motivates the manufacturer to expand production capacity but also preserves the retailer's flexibility.