Multi-Product Production System with the Reduced Failure Rate and the Optimum Energy Consumption under Variable Demand

The advertising of any smart product is crucial in generating customer demand, along with reducing sale prices. Naturally, a decrease in price always increases the demand for any smart product. This study introduces a multi-product production process, taking into consideration the advertising- and price-dependent demands of products, where the failure rate of the production system is reduced under the optimum energy consumption. For long-run production systems, unusual energy consumption and machine failures occur frequently, which are reduced in this study. All costs related with the production system are included in the optimum energy costs. The unit production cost is dependent on the production rate of the machine and its failure rate. The aim of this study is to obtain the optimum profit with a reduced failure rate, under the optimum advertising costs and the optimum sale price. The total profit of the model becomes a complex, non-linear function, with respect to the decision variables. For this reason, the model is solved numerically by an iterative method. However, the global optimality is proved numerically, by using the Hessian matrix. The numerical results obtained show that for smart production, the maximum profit always occurs at the optimum values of the decision variables.

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Effect of Energy and Failure Rate in a Multi-Item Smart Production System

Energies ◽

10.3390/en11112958 ◽

2018 ◽

Vol 11 (11) ◽

pp. 2958 ◽

Cited By ~ 11

Author(s):

Mitali Sarkar ◽

Biswajit Sarkar ◽

Muhammad Iqbal

Keyword(s):

Energy Consumption ◽

Production Rate ◽

Failure Rate ◽

Production System ◽

Optimal Solution ◽

Development Cost ◽

Lot Size ◽

Defective Items ◽

Unusual Amount ◽

Control State

To form a smart production system, the effect of energy and machines’ failure rate plays an important role. The main issue is to make a smart production system for complex products that the system may produce several defective items during a long-run production process with an unusual amount of energy consumption. The aim of the model is to obtain the optimum amount of smart lot, the production rate, and the failure rate under the effect of energy. This study contains a multi-item economic imperfect production lot size energy model considering a failure rate as a system design variable under a budget and a space constraint. The model assumes an inspection cost to ensure product’s quality under perfect energy consumption. Failure rate and smart production rate dependent development cost under energy consumption are considered, i.e., lower values of failure rate give higher values of development cost and vice versa under the effect of proper utilization of energy. The manufacturing system moves from in-control state to out-of-control state at a random time. The theory of nonlinear optimization (Kuhn–Tucker method) is employed to solve the model. There is a lemma to obtain the global optimal solution for the model. Two numerical examples, graphical representations, and sensitivity analysis of key parameters are given to illustrate the model.

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Optimization of Safety Stock under Controllable Production Rate and Energy Consumption in an Automated Smart Production Management

Energies ◽

10.3390/en12112059 ◽

2019 ◽

Vol 12 (11) ◽

pp. 2059 ◽

Cited By ~ 4

Author(s):

Mitali Sarkar ◽

Biswajit Sarkar

Keyword(s):

Energy Consumption ◽

Production Rate ◽

Production System ◽

Spare Parts ◽

Energy Utilization ◽

Smart Manufacturing ◽

Defective Items ◽

Safety Stock ◽

Random Breakdown ◽

Optimum Energy

A smart production system is essential to produce complex products under the consumption of efficient energy. The main ramification of controllable production rate, amount of production size, and safety stocks is simultaneously optimized under proper utilization of energy within a smart production system with a random breakdown of spare parts. Due to the random breakdown, a greater amount of energy may be used. For this purpose, this study is concerned about the optimum safety stock level under the exact amount of energy utilization. For random breakdown, there are three cases as production inventory meets the demand without utilization of the safety stock, with using of the safety stock, and consumed the total safety stock amount and facing shortages. After the random breakdown time, the smart production system may move to an out-of-control state and may produce defective items, where the production rate of defective items is a random variable, which follows an exponential distribution. The total cost is highly nonlinear and cannot be solved by any classical optimization technique. A mathematical optimization tool is utilized to test the model. Numerical study proves that the effect of energy plays an important role for the smart manufacturing system even though random breakdowns are there. it is found that the controllable production rate under the effect of the optimum energy consumption really effects significantly in the minimization cost. It saves cost regarding the corrective and preventive maintenance cost. The amount of safety stock can have more support under the effect of optimum energy utilization. The energy can be replaced by the solar energy.

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Energy Consumption and Its Structures in Food Production Systems of the Visegrad Group Countries Compared with EU-15 Countries

Energies ◽

10.3390/en14133945 ◽

2021 ◽

Vol 14 (13) ◽

pp. 3945

Author(s):

Bartłomiej Bajan ◽

Joanna Łukasiewicz ◽

Aldona Mrówczyńska-Kamińska

Keyword(s):

Energy Consumption ◽

Production System ◽

Food Production ◽

Energy Use ◽

Production Systems ◽

The European Union ◽

Input Output ◽

Visegrad Group ◽

Food Production System ◽

The Eu

While joining the European Union (EU) in 2004, the countries of the Visegrad Group (V4) had to face a major challenge in the context of adapting to the EU standards in the field of energy use and energy efficiency. One of the sectors that heavily depends on the use of energy (mainly from fossil fuels) is the food production system, whose energy transformation is essential for future food security. The study aimed to measure the use of energy and its structures in the food production systems of the V4 countries and the EU-15 countries in relation to the implementation of the EU energy targets. The targets assumed, among other things, a reduction in overall energy use and an increase in the share of renewables in the energy mix. The proprietary method based on the assumptions of lifecycle assessment was applied to measure energy consumption in the food production systems with the use of input–output tables and energy accounts, which are part of the World Input–Output Database. The research shows a decreasing share of the food production systems in energy use of the V4 countries, while in the EU-15 countries, it remains on average at a stable, low level (around 4.4%). The discussed share for Poland averaged 8.8% in the period considered, for Hungary 7.6%, for the Czech Republic 3.8%, and for Slovakia 3.3%. The share of renewables in energy use of the food production systems is growing. However, in some countries of the EU-15, it increases at a slower pace than the assumed strategic goals, mainly in the countries that are the largest food producers in the EU. For Germany, the Netherlands, Spain, and Italy, the average deviation of the share of renewables use in the food production system from the 2020 target for the entire economy is around 12 percentage points. In the case of V4 countries, the share of renewable energy use in food production systems is close to the assumed strategic targets.

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Economic Development, CO2 Emissions and Energy Use Nexus-Evidence from the Danube Region Countries

Energies ◽

10.3390/en14113165 ◽

2021 ◽

Vol 14 (11) ◽

pp. 3165

Author(s):

Eva Litavcová ◽

Jana Chovancová

Keyword(s):

Economic Growth ◽

Energy Consumption ◽

Co2 Emissions ◽

Carbon Emissions ◽

Bounds Testing ◽

Mutual Cooperation ◽

Long Run ◽

Short Run ◽

Danube Region ◽

The Impact

The aim of this study is to examine the empirical cointegration, long-run and short-run dynamics and causal relationships between carbon emissions, energy consumption and economic growth in 14 Danube region countries over the period of 1990–2019. The autoregressive distributed lag (ARDL) bounds testing methodology was applied for each of the examined variables as a dependent variable. Limited by the length of the time series, we excluded two countries from the analysis and obtained valid results for the others for 26 of 36 ARDL models. The ARDL bounds reliably confirmed long-run cointegration between carbon emissions, energy consumption and economic growth in Austria, Czechia, Slovakia, and Slovenia. Economic growth and energy consumption have a significant impact on carbon emissions in the long-run in all of these four countries; in the short-run, the impact of economic growth is significant in Austria. Likewise, when examining cointegration between energy consumption, carbon emissions, and economic growth in the short-run, a significant contribution of CO2 emissions on energy consumptions for seven countries was found as a result of nine valid models. The results contribute to the information base essential for making responsible and informed decisions by policymakers and other stakeholders in individual countries. Moreover, they can serve as a platform for mutual cooperation and cohesion among countries in this region.

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Soil Bacterial Community Diversity and Composition as Affected by Tillage Intensity Treatments in Corn-Soybean Production Systems

Microbiology Research ◽

10.3390/microbiolres12010012 ◽

2021 ◽

Vol 12 (1) ◽

pp. 157-172

Author(s):

Shankar G. Shanmugam ◽

Normie W. Buehring ◽

Jon D. Prevost ◽

William L. Kingery

Keyword(s):

Microbial Community ◽

Bacterial Community ◽

Community Composition ◽

Production System ◽

Soil Microbial Community ◽

Production Systems ◽

Bacterial Community Composition ◽

Soybean Production ◽

Soil Microbial ◽

Soil Bacterial

Our understanding on the effects of tillage intensity on the soil microbial community structure and composition in crop production systems are limited. This study evaluated the soil microbial community composition and diversity under different tillage management systems in an effort to identify management practices that effectively support sustainable agriculture. We report results from a three-year study to determine the effects on changes in soil microbial diversity and composition from four tillage intensity treatments and two residue management treatments in a corn-soybean production system using Illumina high-throughput sequencing of 16S rRNA genes. Soil samples were collected from tillage treatments at locations in the Southern Coastal Plain (Verona, Mississippi, USA) and Southern Mississippi River Alluvium (Stoneville, Mississippi, USA) for soil analysis and bacterial community characterization. Our results indicated that different tillage intensity treatments differentially changed the relative abundances of bacterial phyla. The Mantel test of correlations indicated that differences among bacterial community composition were significantly influenced by tillage regime (rM = 0.39, p ≤ 0.0001). Simpson’s reciprocal diversity index indicated greater bacterial diversity with reduction in tillage intensity for each year and study location. For both study sites, differences in tillage intensity had significant influence on the abundance of Proteobacteria. The shift in the soil bacterial community composition under different tillage systems was strongly correlated to changes in labile carbon pool in the system and how it affected the microbial metabolism. This study indicates that soil management through tillage intensity regime had a profound influence on diversity and composition of soil bacterial communities in a corn-soybean production system.

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A New Procedure of Production Orders Sequencing in Mixed-Model Production Systems

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.1036.864 ◽

2014 ◽

Vol 1036 ◽

pp. 864-868 ◽

Cited By ~ 1

Author(s):

Marcin Zemczak ◽

Damian Krenczyk

Keyword(s):

Task Scheduling ◽

Production System ◽

Mixed Model ◽

Production Systems ◽

Production Capacity ◽

Approximate Solutions ◽

Task Sequence ◽

Optimal Method ◽

Sequencing Problem ◽

Car Sequencing

The paper presents the task scheduling issue, which main aim is to establish a proper sequence of tasks, that would maximize the utilization of companys production capacity. According to the literature sources, the presented sequencing problem, denoted as CSP (Car Sequencing Problem) belongs to the NP-hard class, as has been proven by simple reduction from Hamiltonians Path problem. Optimal method of solution has not yet been found, only approximate solutions have been offered, especially from the range of evolutionary algorithms. Regardless of specific production system, while considering reception of new tasks into the system, current review of the state of the system is required in order to decide whether and when a new order can be accepted for execution. In this paper, the problem of task scheduling is limited to the specific existing mixed-model production system. The main goal is to determine the effective method of creation of task sequence. Through the use of computational algorithms, and automatic analysis of the resulting sequence, rates of production are able to be checked in a real time, and so improvements can be proposed and implemented.

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Using Computer Simulation Method to Improve Throughput of Production Systems by Buffers and Workers Allocation

Management and Production Engineering Review ◽

10.1515/mper-2015-0037 ◽

2015 ◽

Vol 6 (4) ◽

pp. 60-69 ◽

Cited By ~ 2

Author(s):

Sławomir Kłos ◽

Peter Trebuna

Keyword(s):

Computer Simulation ◽

Production System ◽

Production Systems ◽

Simulation Method ◽

System Throughput ◽

Buffer Allocation ◽

Simulation Experiments ◽

Buffer Capacities ◽

The Relationship ◽

Support Decision Making

Abstract This paper proposes the application of computer simulation methods to support decision making regarding intermediate buffer allocations in a series-parallel production line. The simulation model of the production system is based on a real example of a manufacturing company working in the automotive industry. Simulation experiments were conducted for different allocations of buffer capacities and different numbers of employees. The production system consists of three technological operations with intermediate buffers between each operation. The technological operations are carried out using machines and every machine can be operated by one worker. Multi-work in the production system is available (one operator operates several machines). On the basis of the simulation experiments, the relationship between system throughput, buffer allocation and the number of employees is analyzed. Increasing the buffer capacity results in an increase in the average product lifespan. Therefore, in the article a new index is proposed that includes the throughput of the manufacturing system and product life span. Simulation experiments were performed for different configurations of technological operations.

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Application of Statistical Taguchi Method to Optimize Main Elements in the Residential Buildings in Malaysia Based Energy Consumption

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.606.265 ◽

2014 ◽

Vol 606 ◽

pp. 265-269 ◽

Cited By ~ 6

Author(s):

Seyed Mojib Zahraee ◽

Milad Hatami ◽

Ali Asghar Bavafa ◽

Kambiz Ghafourian ◽

Jafri Mohd Rohani

Keyword(s):

Energy Consumption ◽

Taguchi Method ◽

Residential Buildings ◽

Controversial Issues ◽

Upward Trend ◽

Warming Climate ◽

World Energy ◽

Optimum Energy ◽

Temperature And Pressure ◽

World Energy Consumption

Today energy consumption is one of the controversial issues in the world. The rapid growing world energy consumption has already increased concern about the supply problems, heavy environmental effects such as global warming, climate change and etc. One of the most users of energy is residential buildings that consume the biggest share of energy. Growth in population, rising demand for buildings together causes to increase the upward trend in energy consumption. Therefore, energy efficiency in buildings plays a significant role to decrease the environmental effect. The goal of this paper is optimizing the main elements which are window, ceiling and wall by considering the effect of uncontrollable factors such as humidity , temperature and pressure in residential buildings using statistical method namely Taguchi method (JMP 11 software). A two-storey house in Malaysia was selected to simulate by means of BIM application. Based on the result, the optimum energy saving will be achieved when the type of material which are used for wall ,ceiling and window to be Brick Plaster , Acoustic Tile Suspended and Single Glazed Alum Frame respectively.

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Pulsed LED-Lighting as an Alternative Energy Savings Technique for Vertical Farms and Plant Factories

Energies ◽

10.3390/en14061603 ◽

2021 ◽

Vol 14 (6) ◽

pp. 1603

Author(s):

Ernesto Olvera-Gonzalez ◽

Nivia Escalante-Garcia ◽

Deland Myers ◽

Peter Ampim ◽

Eric Obeng ◽

...

Keyword(s):

Energy Consumption ◽

Alternative Energy ◽

Energy Savings ◽

Production Systems ◽

Real Life ◽

Plant Production ◽

Photon Flux ◽

Photon Flux Density ◽

Led Light ◽

Operation Modes

Different strategies are reported in the literature for energy saving in Closed Plant Production Systems (CPPS). However, not reliable evidences about energy consumption with the use of pulsed LED light technique in lighting system available in Plant Factory and Vertical Farm. In this work, three key points to determine the effects of pulsed LED light versus continuous LED light are presented: (1) A mathematical model and its practical application for stabilizing the energy equivalence using LED light in continuous and pulsed mode in different light treatments. (2) The quantum efficiency of the photosystem II was used to determine positive and/or negative effects of the light operating mode (continuous or pulsed) on chili pepper plants (Capsicum annuum var. Serrano). (3) Evaluation of energy consumption with both operation modes using ten recipes from the literature to grow plants applied in Closed Plant Production Systems, different Photosynthetic Photon Flux Density at 50, 110, and 180 µmol m−2 s−1, Frequencies at 100, 500, and 1000 Hz, and Duty Cycles of 40, 50, 60, 70, 80, and 90%. The results show no significant statistical differences between the operation modes (continuous and pulsed LED light). For each light recipe analyzed, a pulsed frequency and a duty cycle were obtained, achieving significant energy savings in every light intensity. The results can be useful guide for real-life applications in CPPS.

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Responsive Production Systems and Roles that Robots can Play

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.62-64.275 ◽

2009 ◽

Vol 62-64 ◽

pp. 275-292

Author(s):

R.H. Weston

Keyword(s):

Building Block ◽

Production System ◽

World Wide ◽

Production Systems ◽

Industrial Robots ◽

Robotic Systems ◽

Different Types ◽

Useful Lifetime

With increased product dynamics world-wide, the average economic lifetime of production systems is falling. Industrial robots are widely assumed to be inherently flexible and therefore that they can function as a programmable building block of response production systems. This paper reviews common capabilities of contemporary industrial robotic systems and investigates their capability to extend the useful lifetime of production system by coping with different types of product dynamic. Also considered are relative capabilities of conventional programmable robots and an emerging generation of programmable and configurable component-based machines.

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