scholarly journals Autonomated Inspection Policy for Smart Factory—An Improved Approach

Mathematics ◽  
2020 ◽  
Vol 8 (10) ◽  
pp. 1815
Author(s):  
Bimal Kumar Sett ◽  
Bikash Koli Dey ◽  
Biswajit Sarkar
Keyword(s):  
Production Rate ◽  
Production System ◽  
Human Error ◽  
Production Systems ◽  
Brand Image ◽  
Selling Price ◽  
Total System ◽  
Production Run ◽  
Special Cases ◽  
Control State

The proposed model focuses on an imperfect production process (IPP) in which, during long-term production, the system may change to an “out-of-control” state from an “in-control” state and produce some imperfect products because of a long production run length. Brand image and industry reputation are affected by product defectiveness. To increase the profit of any industry and improve reputation and brand image, inspection of the production system is required. However, this inspection is subjected to human error, which negatively affects the assessment of production systems. Herein, an error-free inspection is performed with the help of an autonomation policy, in which each product is inspected via a machine instead of a human, facilitating an error-free inspection and converting the production system to a smart production system. Moreover, in reality, product demand cannot always be constant. Therefore, in this model, a selling-price-dependent demand is considered along with a variable production rate to enhance model applicability. Moreover, total system profit is optimized and optimal values for production run time, inspection scheduling, selling price, buffer inventory, and production rate are determined. Finally, for model validation, some numerical examples along with special cases are provided. The concavity of the optimal function is also proven through graphical illustration. The sensitivity of the key parameters of the presented model is explored and the significance is explained.

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

Energies ◽  
2018 ◽  
Vol 11 (11) ◽  
pp. 2958 ◽  
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.

Research on Injection-Production System’s Effectiveness of Completely Fractured Well Arrangement

2011 ◽  
Vol 110-116 ◽  
pp. 2183-2187
Author(s):  
Hua Lin Liu ◽  
Wei Xiong
Keyword(s):  
Pressure Gradient ◽  
Production Rate ◽  
Production System ◽  
Production Systems ◽  
Cost Effective ◽  
Driving Pressure ◽  
Oil Viscosity ◽  
Production Wells ◽  
Effective Development ◽  
Fractured Well

For rapid production decline, difficult production stability ability in low permeability reservoirs, establishment of effective injection-production system between injection and production wells is proposed to curb production decline. The effectiveness of an injection-production system should contain two aspects, supplementing enough energy to layer on time and overcoming starting pressure gradient. Completely fractured injection-production well arrangement is simplified into an injection-production one-way flow model, and layer pressure calculation formula is derived by separating variables while single-phase flow. Formulas of determining terminal parameters and driving pressure gradient of an effective injection-production system are gained by demanding for time limits on layer pressure and letting production well’s B.H.P (bottom hole pressure) equal or a bit bigger than a minimum pressure. Results show that the efficiency of a completely fractured well arrangement is related to permeability, oil viscosity, reservoir thickness, well spacing, well draining, production rate, and maximum producing pressure drop. The bigger the production rate, the smaller well draining should adopt, and the driving pressure gradient will also become bigger. For a certain reservoir, several sets of effective injection-production systems are possible, and which effective injection-production system is the best should determine by the principle of cost-effective development.

Integrated vendor–buyer strategies for imperfect production systems with maintenance and warranty policy

2020 ◽  
Vol 54 (2) ◽  
pp. 435-450 ◽  
Author(s):  
Aditi Khanna ◽  
Prerna Gautam ◽  
Biswajit Sarkar ◽  
Chandra K. Jaggi
Keyword(s):  
Production System ◽  
Preventive Maintenance ◽  
Production Systems ◽  
Cost Minimization ◽  
Efficient Operation ◽  
Reduced Gradient Method ◽  
Integrated Cost ◽  
Generalized Reduced Gradient ◽  
Cost Minimization Problem ◽  
Control State

Collaboration has evolved as a key component of many modern supply chains, supporting the competitive advantages of companies in a range of operations from manufacturing to sales. With this viewpoint, the present paper develops an integrated inventory model in which manufacturing is carried out at the vendor’s end so as to fulfill demand at the buyer’s doorway. As the production process is presumed to be imperfect it shifts from an “in-control” state to “out-of-control” state at any random time and yields non-conforming items. The vendor uses regular preventive maintenance actions for the efficient operation of the production system and offers free minimal repair warranty on the products sold to the buyer. Along with preventive maintenance actions the vendor also uses the rework process and restoration process as effective steps towards minimizing the imperfections of the production system. The proposed model solves the non-linear cost minimization problem through a generalized reduced gradient method by using Lingo 15.0. The aim is to jointly optimize the order size, backorder size and the number of shipments in order to minimize the integrated cost of the vendor and the buyer. Numerical analysis and sensitivity analysis is performed on key parameters that render some important supervisory insights.

scholarly journals Adjustment of credit period and stock-dependent demands in a supply chain model with variable imperfectness

2021 ◽  
Author(s):  
Ateka Banu ◽  
Amalesh Kumar Manna ◽  
Shyamal Kumar Mondal
Keyword(s):  
Production Rate ◽  
Demand Function ◽  
Chain Model ◽  
Stock Level ◽  
Credit Period ◽  
Production Run ◽  
Demand Factor ◽  
Supply Chain Model ◽  
Control State ◽  
Dependent Demand

In this model, a supply chain model has been developed where a manufacturer continuously transports perfect quality items at no cost to a distribution center to maintain the market demand. At the beginning of the process, the production process is in an "in-control" state, but after a random time, it goes to an "out-of-control" state. Thus the production process produces perfect as well as imperfect items in this state. The rate of imperfect production depends on production rate and production-run length in the "out-of-control" state. The unit production cost of the manufacturer depends on the production rate which indicates that the higher production rate is the cause of higher production cost if it exceeds the normal production rate set by the manufacturer. The manufacturer provides a credit period to the distributor to increase his sales growth. In the competitive business world, credit period affects the demand rate of a retailer/buyer due to its late payment facility. So, here, credit period dependent demand function is introduced for the distributor. During the festive season, demand factor of products is usually affected by stock level. Also, for some types of products (such as clothing), the demand factor depends on its stock level. Thus we have considered stock-dependent demand function for the customers. Now, in an infinite time horizon, the problem is how they adjust their demands to sustain the whole system's financial  flow. The novelty of this model is to analyze the compatibility of this two-type of demand in their businesses so that both can maintain their profits. Also, there is another credit length which is offered by the distributor. The proposed model has been discussed in type-2 fuzzy environment due to the uncertainty of the credit period. The purpose of this model is to optimize the integrated profit of the system by optimizing production rate and production-run time. Finally, numerical examples have been provided to illustrate the feasibility of both crisp and fuzzy model and some conclusions are derived conducting a sensitivity analysis of different parameters.

scholarly journals Comparison of Carbon Footprint and Variable Costs of Selected Nursery Production Systems for a 5-cm-caliper Red Maple

HortScience ◽  
2016 ◽  
Vol 51 (4) ◽  
pp. 383-387 ◽  
Author(s):  
Dewayne L. Ingram ◽  
Charles R. Hall
Keyword(s):  
Life Cycle ◽  
Production System ◽  
Production Systems ◽  
Cultural Practice ◽  
Variable Cost ◽  
Total System ◽  
Red Maple ◽  
Production Methods ◽  
Nursery Production ◽  
Materials Used

The objective of this study was to examine the differences in global warming potential (GWP) and variable cost structure of a 5-cm-caliper red maple tree grown using two alternative production methods including a traditional field [balled and burlapped (BNB)] production system and a containerized, pot-in-pot (PIP) production system. Feedback from nursery growers was obtained to model each production system including the labor required for each cultural practice, materials used, and the hourly usage of tractors and other equipment. Findings from the study indicate that the total system GWP and variable cost for the PIP tree system is −671.42 kg of carbon dioxide equivalent (CO2e) and $250.76, respectively, meaning that the tree sequesters much more carbon during its life than is emitted during its entire life cycle. The same holds true for the BNB tree; however, in this system, the GWP of the tree −666.15 kg CO2e during its life cycle at a total variable cost of $236.13. Thus, the BNB tree costs slightly less to produce than its PIP counterpart but the life cycle GWP is slightly less positive as well.

scholarly journals Determination of economic stocking rates for beef cattle grazing stargrass under two fertilizer levels

1969 ◽  
Vol 76 (3-4) ◽  
pp. 131-150
Author(s):  
Mariano Antoni ◽  
Rafael Ramos ◽  
Américo Casas ◽  
Eugenio Marrero
Keyword(s):  
Production System ◽  
Production Systems ◽  
Cattle Grazing ◽  
Meat Production ◽  
Selling Price ◽  
Stocking Rate ◽  
Economic Returns ◽  
Wide Range ◽  
Fertilizer System ◽  
Stocking Rates

Two meat production systems based on cattle grazing stargrass pastures under two fertilization levels were evaluated to determine which production system, stocking rate level, and selling time could be better used under different price scenarios to achieve maximum economic returns. Based on the findings of R. J. Jones and R. S. Sandland and other authors, it was assumed that the relationship between stocking rate and animal weight gain can be best represented by a simple linear model of the form y = a -bx over a wide range of stocking rates. To determine the equation parameters each system was grazed at three stocking rates and the straight line equation fitted at different periods. The price scenario prevailing at the conclusion of the study favored the utilization of the low fertilization system with a stocking rate close to 3.8 animals per hectare and selling the animals after 10 to 11 grazing months. This stocking rate should be lowered to 3.6 animals per hectare if a minimum finishing weight of 454 kg is required because of a 5% price discount for lighter animals. However, improvement on the price spread between animal purchase and selling price, or relatively sharp increase in meat price in relation to the fertilizer price could justify the utilization of the more capital intensive high fertilizer system. The selection of a particular production system and stocking rate should not be made independently of the current price levels since the latter will ultimately determine the success and failure of the system.

scholarly journals A Sustainable Online-to-Offline (O2O) Retailing Strategy for a Supply Chain Management under Controllable Lead Time and Variable Demand

2021 ◽  
Vol 13 (4) ◽  
pp. 1756
Author(s):  
Biswajit Sarkar ◽  
Bikash Koli Dey ◽  
Mitali Sarkar ◽  
Ali AlArjani
Keyword(s):  
Lead Time ◽  
Critical Parameters ◽  
Selling Price ◽  
Total System ◽  
Global Optimality ◽  
Chain Management ◽  
Numerical Examples ◽  
Controllable Lead Time ◽  
Special Cases ◽  
Distribution Free Approach

Every industry always tries to provide the best service to its consumers. To provide better service to the consumer and optimize profit, a sustainable online-to-offline retailing strategy is proposed in this current study. Both online and offline systems are considered here, i.e., to provide the best service, the industry sells its products online and offline. Due to the consideration of online and offline systems, the selling price of the products is also different for different modes, and the demand for a particular product is the combined demand of online demand and offline demand, which depend on the selling price of the product. Moreover, the exact lead time and exact backorder are calculated to obtain the system’s exact cost or profit, which directly improves the system’s service. Different investments are incorporated to optimize the total system profit. A distribution-free approach is utilized to solve this model. Numerical examples are provided to prove the applicability of the model in reality. Sensitivity analysis is performed based on critical parameters. Special cases and graphical representations also prove the global optimality of the current study.

PERFORMANCE EVALUATION OF GENETIC DISTRIBUTED FUZZY CONTROLLERS FOR MULTI-PART-TYPE PRODUCTION LINE

2007 ◽  
Vol 06 (02) ◽  
pp. 115-128
Author(s):  
SEYED MAHDI HOMAYOUNI ◽  
TANG SAI HONG ◽  
NAPSIAH ISMAIL
Keyword(s):  
Genetic Algorithm ◽  
Performance Evaluation ◽  
Objective Function ◽  
Production Rate ◽  
Production Line ◽  
Production Systems ◽  
Membership Functions ◽  
Part Type ◽  
High Penalty ◽  
Single Part

Genetic distributed fuzzy (GDF) controllers are proposed for multi-part-type production line. These production systems can produce more than one part type. For these systems, "production rate" and "priority of production" for each part type is determined by production controllers. The GDF controllers have already been applied to single-part-type production systems. The methodology is illustrated and evaluated using a two-part-type production line. For these controllers, genetic algorithm (GA) is used to tune the membership functions (MFs) of GDF. The objective function of the GDF controllers minimizes the surplus level in production line. The results show that GDF controllers can improve the performance of production systems. GDF controllers show their abilities in reducing the backlog level. In production systems in which the backlog has a high penalty or is not allowed, the implementation of GDF controllers is advisable.

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

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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