scholarly journals A New Green Efficiency-Based Carbon Taxing Policy and Its Effects on a Production-Inventory System with Random Carbon Emissions and Green Investment

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Tapan Kumar Datta
Keyword(s):  
Carbon Tax ◽  
Profit Maximization ◽  
Inventory System ◽  
Environmental Benefits ◽  
Independent Random Variables ◽  
Model Parameters ◽  
Green Technologies ◽  
Numerical Examples ◽  
Production Inventory ◽  
Production Inventory System

In this study, the author proposes a new carbon taxing policy. This proposed carbon tax has two tax components. The first component is constant, and the second component depends on the green efficiency of production. The green efficiency of production is measured by the average amount of emissions per unit production in an assessment year. The green efficiency-based tax component can be reset every year. Lesser average emission rate indicates better green efficiency. The second component of this proposed carbon tax forces the firm to improve the green efficiency of production, which results in cleaner production. The author incorporates this new carbon tax policy in a production-inventory system with a price-sensitive demand rate. A rule is provided for the implementation of this new tax. Emissions during setup, production, and storage are considered as independent random variables. The firm has the opportunity of investing in green technologies to improve green efficiency. A profit maximization policy is adopted to solve the developed model. A solution algorithm is also provided. The model is illustrated by numerical examples with randomly generated model parameters. The results of numerical examples show the environmental benefits of the proposed carbon tax.

scholarly journals Optimal Maintenance of a Production-inventory System With Continuous Repair Times and Idle Periods

2020 ◽  
Vol Volume 14 ◽  
Keyword(s):  
Preventive Maintenance ◽  
Average Cost ◽  
Inventory System ◽  
Control Limit ◽  
Raw Material ◽  
Production Unit ◽  
Numerical Examples ◽  
Long Run ◽  
Production Inventory ◽  
Production Inventory System

In this paper two similar models for the maintenance of a production-inventory system are considered. In both models, an input generating installation supplies a buffer with a raw material and a production unit pulls the raw material from the buffer. The installation in the first model and the production unit in the second model deteriorate stochastically over time and the problem of their optimal preventive maintenance is considered. In the first model, it is assumed that the installation, after the completion of its maintenance, remains idle until the buffer is evacuated, while in the second model, it is assumed that the production unit, after the completion of its maintenance, remains idle until the buffer is filled up. The preventive and corrective repair times of the installation in the first model and the preventive and corrective repair times of the production unit in the second model are continuous random variables with known probability density functions. Under a suitable cost structure, semi-Markov decision processes are considered for both models in order to find a policy that minimizes the long-run expected average cost per unit time. A great number of numerical examples provide strong evidence that, for each fixed buffer content, the average-cost optimal policy is of control-limit type in both models, i.e. it prescribes a preventive maintenance of the installation in the first model and a preventive maintenance of the production unit in the second model if and only if their degree of deterioration is greater than or equal to a critical level. Using the usual regenerative argument, the average cost of the optimal control-limit policy is computed exactly in both models. Four numerical examples are also presented in which the preventive and corrective repair times follow the Exponential, the Weibull, the Gamma and the Log-Normal distribution, respectively.

Control of a production-inventory system using a PID controller and demand prediction

2008 ◽  
Vol 41 (2) ◽  
pp. 1869-1874 ◽  
Author(s):  
Santiago Tosetti ◽  
Daniel Patiño ◽  
Flavio Capraro ◽  
Adrian Gambier
Keyword(s):  
Pid Controller ◽  
Inventory System ◽  
Demand Prediction ◽  
Production Inventory ◽  
Production Inventory System

An Imperfect Production Model for Breakable Multi-Item with Dynamic Demand and Learning Effect on Rework over Random Planning Horizon

2021 ◽  
Vol 14 (12) ◽  
pp. 574
Author(s):  
Amalesh Kumar Manna ◽  
Leopoldo Eduardo Cárdenas-Barrón ◽  
Barun Das ◽  
Ali Akbar Shaikh ◽  
Armando Céspedes-Mota ◽  
...  
Keyword(s):  
Learning Effect ◽  
Planning Horizon ◽  
Inventory Model ◽  
Inventory System ◽  
Production Model ◽  
Inventory Models ◽  
Imperfect Production ◽  
Production Inventory ◽  
Random Planning Horizon ◽  
Production Inventory System

In recent times, in the literature of inventory management there exists a notorious interest in production-inventory models focused on imperfect production processes with a deterministic time horizon. Nevertheless, it is well-known that there is a high influence and impact caused by the learning effect on the production-inventory models in the random planning horizon. This research work formulates a mathematical model for a re-workable multi-item production-inventory system, in which the demand of the items depends on the accessible stock and selling revenue. The production-inventory model allows shortages and these are partial backlogged over a random planning horizon. Also, the learning effect on the rework policy, inflation, and the time value of money are considered. The main aim is to determine the optimum production rates that minimize the expected total cost of the multi-item production-inventory system. A numerical example is solved and a detailed sensitivity analysis is conducted in order to study the production-inventory model.

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