scholarly journals An Automated Smart EPQ-Based Inventory Model for Technology-Dependent Products under Stochastic Failure and Repair Rate

Symmetry ◽  
2020 ◽  
Vol 12 (3) ◽  
pp. 388 ◽  
Author(s):  
Iqra Asghar ◽  
Jong Soo Kim
Keyword(s):  
Mathematical Model ◽  
Production Rate ◽  
Production Efficiency ◽  
Manufacturing System ◽  
Manufacturing Technology ◽  
Repair Time ◽  
High Tech ◽  
Performance Quality ◽  
Maintenance Model ◽  
Variable Production

With the ever-growing technology development, high-tech products such as mobile phones, computers, electromagnetic devices and smart devices are facing high design and production modification requirements with relatively shorter life cycles. For instance, every forthcoming smart phone goes out of production in a shorter period after its launch, followed by its next generation. The design of high-tech products requires high investments in smart and automated manufacturing technology to ensure higher production efficiency. For high-tech products with short life spans, the manufacturing performance-quality variable is an important design parameter that affects system reliability, production efficiency and manufacturing costs. Major performance-quality factors of a manufacturing system which affect productivity and reliability of the manufacturing process are discussed in this research. The study investigates an integrated smart production maintenance model under stochastic manufacturing reliability for technology dependent demand and variable production rate. The smart unit production cost is a function of manufacturing reliability and controllable production rate, as a manufacturing system can be operated at different production rates within designed limits μ ϵ [ μ m i n , μ m a x ] . Manufacturing reliability is increased through investment in smart manufacturing technology and resources. The integrated smart production maintenance model is formulated under general failure and repair time distributions and the optimal production maintenance policy is investigated under specific failure and repair time distributions. A mathematical model is developed to optimize the manufacturing quality-performance parameter, variable production rate, per unit technology investment and production lot size. The total cost function is optimized through the Khun–Tucker method. The mathematical model is also validated with numerical analysis, comparative study, and sensitivity analysis for model key parameters.

scholarly journals Production Inventory Model under Time Dependent Demand, Uneven Manufacturing Rate and Manufacture Time Dependent Selling Price

2021 ◽  
Vol 23 (04) ◽  
pp. 225-237
Author(s):  
G.S. Buttar ◽  
◽  
Ruchi Sharma Sharma ◽  
Keyword(s):  
Production Rate ◽  
Production Efficiency ◽  
Inventory Model ◽  
Time Dependent ◽  
Selling Price ◽  
Production Inventory ◽  
Efficiency Cost ◽  
Manufacturing Time ◽  
Variable Production ◽  
Dependent Demand

In this paper, an inventory model for production of a single article with an uneven manufacturing rate and manufacturing time subsidiary selling cost has been considered. The considered production inventory model is accepted to create perfect items in beginning however because of different elements, after some time the production begins diminishing exponentially with time, i.e., the variable production rate has been thought of. The demand is time subordinate. Initially up to certain time, production rate remains constant. But after some time, due to various factors, production will decrease. Therefore, the efficiency (E) of such factors must be increased to get more production which can maintain the production efficiency cost which has been applied. Considering this fact inverse efficiency λ has been introduced in production rate. By utilizing differential calculus, expected maximum profit has been resolved. The goal of the examination is to decide the ideal arrangement for a production framework that expands the total benefit subject to certain limitations viable. Results are examined by means of a mathematical example to outline the hypothesis.

scholarly journals Economic Analysis of an Integrated Production–Inventory System under Stochastic Production Capacity and Energy Consumption

Energies ◽  
2019 ◽  
Vol 12 (16) ◽  
pp. 3179 ◽  
Author(s):  
Iqra Asghar ◽  
Biswajit Sarkar ◽  
Sung-jun Kim
Keyword(s):  
Energy Consumption ◽  
Production Rate ◽  
Manufacturing System ◽  
Production Capacity ◽  
Repair Time ◽  
Model Parameters ◽  
Power Cost ◽  
Integrated Production ◽  
Production Inventory ◽  
Stochastic Production

Expensive power cost is a significant concern in today’s manufacturing world. Reduction in energy consumption is an ultimate measure towards achieving manufacturing efficiency and emissions control. In the existing literature of scheduling problems, the consumption of energy is considered uncertain under the dimensions of uncertain demand and supply. In reality, it is a random parameter that also depends on production capacity, manufacturing technology, and operational condition of the manufacturing system. As the unit production cost varies with production rate and reliability of the manufacturing system, the energy consumption of the system also varies accordingly. Therefore, this study investigated an unreliable manufacturing system under stochastic production capacities and energy consumption. A stochastic production–inventory policy is developed to optimize production quantity, production rate, and manufacturing reliability under variable energy consumption costs. As energy consumption varies in different operational states of manufacturing, we consider three specific states of power consumption, namely working, idle, and repair time, for an integrated production–maintenance model. The considered production system is subjected to stochastic failure and repair time, where productivity and manufacturing reliability is improved through additional technology investment. The robustness of the model is shown through numerical example, comparative study, and sensitivity analysis of model parameters. Several graphical illustrations are also provided to obtain meaningful managerial insights.

Research on a Generating Method of Spiral Flutes of Hourglass Worm Gear Hob

2017 ◽  
Author(s):  
Yang Jie ◽  
Li Haitao ◽  
Rui Chengjie ◽  
Wei Wenjun ◽  
Dong Xuezhu
Keyword(s):  
Mathematical Model ◽  
Manufacturing System ◽  
Worm Gear ◽  
Virtual Manufacturing ◽  
Transmission Ratio ◽  
Method Of Determination ◽  
Generating Method ◽  
Multiple Threads ◽  
Different Shapes

All of the cutting edges on an hourglass worm gear hob have different shapes and spiral angles. If the spiral angles are small, straight flutes are usually adopted. But for the hob with multiple threads, the absolute values of the negative rake angles at one side of the cutting teeth will greatly affect the cutting performance of the hob if straight flutes are still used. Therefore, spiral flutes are usually adopted to solve the problem. However, no method of determination of the spiral flute of the hourglass worm gear hob has been put forward till now. Based on the curved surface generating theory and the hourglass worm forming principle, a generating method for the spiral flute of the planar double enveloping worm gear hob is put forward in this paper. A mathematical model is built to generate the spiral flute. The rake angles of all cutting teeth of the hob are calculated. The laws of the rake angles of the cutting teeth of four hobs with different threads from one to four threads are analyzed when straight flutes and spiral flutes are adopted respectively. The laws between the value of the negative rake angles of the hob with four threads and the milling transmission ratio are studied. The most appropriate milling transmission ratio for generating the spiral flute is obtained. The machining of the spiral flutes is simulated by a virtual manufacturing system and the results verify the correctness of the method.

scholarly journals A COVID-19 Supply Chain Management Strategy Based on Variable Production under Uncertain Environment Conditions

2021 ◽  
Vol 18 (4) ◽  
pp. 1662
Author(s):  
Mohammed Alkahtani ◽  
Muhammad Omair ◽  
Qazi Salman Khalid ◽  
Ghulam Hussain ◽  
Imran Ahmad ◽  
...  
Keyword(s):  
Supply Chain ◽  
Supply Chain Management ◽  
Production Rate ◽  
Manufacturing System ◽  
Working Environment ◽  
Data Set ◽  
Manufacturing Firm ◽  
Chain Management ◽  
Ripple Effects ◽  
Multi Stage

The management of a controllable production in the manufacturing system is essential to achieve viable advantages, particularly during emergency conditions. Disasters, either man-made or natural, affect production and supply chains negatively with perilous effects. On the other hand, flexibility and resilience to manage the perpetuated risks in a manufacturing system are vital for achieving a controllable production rate. Still, these performances are strongly dependent on the multi-criteria decision making in the working environment with the policies launched during the crisis. Undoubtedly, health stability in a society generates ripple effects in the supply chain due to high demand fluctuation, likewise due to the Coronavirus disease-2019 (COVID-19) pandemic. Incorporation of dependent demand factors to manage the risk from uncertainty during this pandemic has been a challenge to achieve a viable profit for the supply chain partners. A non-linear supply chain management model is developed with a controllable production rate to provide an economic benefit to the manufacturing firm in terms of the optimized total cost of production and to deal with the different situations under variable demand. The costs in the model are set as fuzzy to cope up with the uncertain conditions created by lasting pandemic. A numerical experiment is performed by utilizing the data set of the multi-stage manufacturing firm. The optimal results provide support for the industrial managers based on the proactive plan by the optimal utilization of the resources and controllable production rate to cope with the emergencies in a pandemic.

scholarly journals Innovations in anaerobic digestion: a model-based study

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Karol Postawa ◽  
Jerzy Szczygieł ◽  
Marek Kułażyński
Keyword(s):  
Mathematical Model ◽  
Anaerobic Digestion ◽  
Production Efficiency ◽  
Biogas Production ◽  
Biogas Plant ◽  
Methane Content ◽  
Pig Manure ◽  
Pig Slurry ◽  
Production Chain ◽  
The Impact

Abstract Background Increasing the efficiency of the biogas production process is possible by modifying the technological installations of the biogas plant. In this study, specific solutions based on a mathematical model that lead to favorable results were proposed. Three configurations were considered: classical anaerobic digestion (AD) and its two modifications, two-phase AD (TPAD) and autogenerative high-pressure digestion (AHPD). The model has been validated based on measurements from a biogas plant located in Poland. Afterward, the TPAD and AHPD concepts were numerically tested for the same volume and feeding conditions. Results The TPAD system increased the overall biogas production from 9.06 to 9.59%, depending on the feedstock composition, while the content of methane was slightly lower in the whole production chain. On the other hand, the AHPD provided the best purity of the produced fuel, in which a methane content value of 82.13% was reached. At the same time, the overpressure leads to a decrease of around 7.5% in the volumetric production efficiency. The study indicated that the dilution of maize silage with pig manure, instead of water, can have significant benefits in the selected configurations. The content of pig slurry strengthens the impact of the selected process modifications—in the first case, by increasing the production efficiency, and in the second, by improving the methane content in the biogas. Conclusions The proposed mathematical model of the AD process proved to be a valuable tool for the description and design of biogas plant. The analysis shows that the overall impact of the presented process modifications is mutually opposite. The feedstock composition has a moderate and unsteady impact on the production profile, in the tested modifications. The dilution with pig manure, instead of water, leads to a slightly better efficiency in the classical configuration. For the TPAD process, the trend is very similar, but the AHPD biogas plant indicates a reverse tendency. Overall, the recommendation from this article is to use the AHPD concept if the composition of the biogas is the most important. In the case in which the performance is the most important factor, it is favorable to use the TPAD configuration.

Underground Gas Storage Inventory Analysis by a Noniterative Method

2004 ◽  
Vol 127 (2) ◽  
pp. 163-165 ◽  
Author(s):  
Ning Liu ◽  
Faruk Civan
Keyword(s):  
Production Rate ◽  
Gas Storage ◽  
Solution Algorithm ◽  
System Model ◽  
Inventory Analysis ◽  
Underground Gas Storage ◽  
Temperature Conditions ◽  
Practical Model ◽  
Variable Production

Underground gas storage inventory and conditions are predicted using a practical model and a noniterative solution algorithm. Various simulation scenarios concerning underground gas storage in depleted reservoirs with variable production rate and temperature conditions demonstrate the effectiveness of this approach. It is shown that the gas storage parameters can be determined conveniently by solving the system model directly without resorting to the tedious procedures of the previous approaches.

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