scholarly journals Green Production Planning and Control for the Textile Industry by Using Mathematical Programming and Industry 4.0 Techniques

Energies ◽  
2018 ◽  
Vol 11 (8) ◽  
pp. 2072 ◽  
Author(s):  
Wen-Hsien Tsai
Keyword(s):  
Mathematical Programming ◽  
Textile Industry ◽  
Industry 4.0 ◽  
Programming Model ◽  
Environmental Issues ◽  
Mathematical Programming Model ◽  
Waste Reuse ◽  
Planning And Control ◽  
Green Production ◽  
And Control

The textile industry is one of the world’s major sources of industrial pollution, and related environmental issues are becoming an ever greater concern. This paper considers the environmental issues of carbon emissions, energy recycling, and waste reuse, and uses a mathematical programming model with Activity-Based Costing (ABC) and the Theory of Constraints (TOC) to achieve profit maximization. This paper discusses the combination of mathematical programming and Industry 4.0 techniques to achieve the purpose of green production planning and control for the textile industry in the new era. The mathematical programming model is used to determine the optimal product mix under various production constraints, while Industry 4.0 techniques are used to control the production progress to achieve the planning targets. With the help of an Industry 4.0 real-time sensor and detection system, it can achieve the purposes of recycling waste, reducing carbon emission, saving energy and cost, and finally achieving a maximization of profit. The main contributions of this research are using mathematical programming approach to formulate the decision model with ABC cost data and TOC constraints for the textile companies and clarifying the relation between mathematical programming models and Industry 4.0 techniques. Managers in the textile companies can apply this decision model to achieve the optimal product-mix under various constraints and to evaluate the effect on profit of carbon emissions, energy recycling, waste reuse, and material quantity discount.

scholarly journals A Framework of Production Planning and Control with Carbon Tax under Industry 4.0

2018 ◽  
Vol 10 (9) ◽  
pp. 3221 ◽  
Author(s):  
Wen-Hsien Tsai ◽  
Yin-Hwa Lu
Keyword(s):  
Production Planning ◽  
Industry 4.0 ◽  
Programming Model ◽  
Carbon Tax ◽  
Optimal Solution ◽  
Production Planning And Control ◽  
Mathematical Programming Model ◽  
Tire Industry ◽  
Planning And Control ◽  
And Control

In recent years, the international community has placed great emphasis on environmental protection issues. The United Nations has also successively enacted relevant laws and regulations to restrain international greenhouse gas emissions and some countries implemented carbon tax levies to reduce air pollution. The tire industry is a manufacturing industry with high pollution and high carbon emissions; therefore, the purpose of this paper is to propose a framework of production planning and control with carbon tax under Industry 4.0 and use the tire industry as the illustrative example. In this framework, the mathematical programming model, with Activity-Based Costing (ABC) and Theory of Constraints (TOC) for production planning, is used to achieve the optimal solution under various production and sale constraints in order to find the optimal product-mix maximizing the profit. On the other hand, Industry 4.0 utilizes new technologies such as 3D printing, robot and automated guided vehicle (AGV) and links all the components in the manufacturing systems by using various sensor systems, Cyber-Physical Systems (CPS) and Internet of Things (IoT) to collect and monitor the activity data of all the components in real-time, to give intelligent responses to various problems that may arise in the factory by the real-time analysis results of cloud computing and big data and to attain the various benefits of Industry 4.0 implementation. The parameters of the mathematical programming model will be updated periodically from the new big data set. In this paper, an illustrative example is used is used to demonstrate the application of the model. From the optimal solution and sensitivity analyses on increasing the raw material’s prices and carbon taxes will affect the profits. This framework can provide a general approach to help companies execute production management in the way of more efficiency, less cost, lower carbon emission and higher quality across the value chain for the tire industry and other industries.

scholarly journals Green Activity-Based Costing Production Decision Model for Recycled Paper

Energies ◽  
2020 ◽  
Vol 13 (10) ◽  
pp. 2413 ◽  
Author(s):  
Chu-Lun Hsieh ◽  
Wen-Hsien Tsai ◽  
Yao-Chung Chang
Keyword(s):  
Mathematical Programming ◽  
Programming Model ◽  
Paper Industry ◽  
Labor Cost ◽  
Production Model ◽  
Theory Of Constraints ◽  
Carbon Equivalent ◽  
Activity Based Costing ◽  
Recycled Paper ◽  
Green Production

Using mathematical programming with activity-based costing (ABC) and based on the theory of constraints (TOC), this study proposed a green production model for the traditional paper industry to achieve the purpose of energy saving and carbon emission reduction. The mathematical programming model presented in this paper considers (1) revenue of main products and byproducts, (2) unit-level, batch-level, and product-level activity costs in ABC, (3) labor cost with overtime available, (4) machine cost with capacity expansion, (5) saved electric power and steam costs by using the coal as the main fuel in conjunction with Refuse Derived Fuel (RDF). This model also considers the constraint of the quantity of carbon equivalent of various gases that are allowed to be emitted from the mill paper-making process to conform to the environmental protection policy. A numerical example is used to demonstrate how to apply the model presented in this paper. In addition, sensitivity analysis on the key parameters of the model are used to provide further insights for this research.

scholarly journals A Mathematical Programming Model to Determine Objective Weights for the Interval Extension of TOPSIS

2018 ◽  
Vol 2018 ◽  
pp. 1-6 ◽  
Author(s):  
Hai Shen ◽  
Lingyu Hu ◽  
Kin Keung Lai
Keyword(s):  
Mathematical Programming ◽  
Input Data ◽  
Programming Model ◽  
Multiple Criteria Decision Making ◽  
Decision Makers ◽  
Mathematical Programming Model ◽  
Topsis Method ◽  
Data Set ◽  
Interval Extension ◽  
Interval Valued

Technique for Order Performance by Similarity to Ideal Solution (TOPSIS) method has been extended in previous literature to consider the situation with interval input data. However, the weights associated with criteria are still subjectively assigned by decision makers. This paper develops a mathematical programming model to determine objective weights for the implementation of interval extension of TOPSIS. Our method not only takes into account the optimization of interval-valued Multiple Criteria Decision Making (MCDM) problems, but also determines the weights only based upon the data set itself. An illustrative example is performed to compare our results with that of existing literature.

scholarly journals Supply chain resilience and industry 4.0: a evaluation of the Brazilian northeast automotive OEM scenario post COVID-19

2021 ◽  
Vol 3 (1) ◽  
Author(s):  
Milton C. Soares ◽  
Cristiano V. Ferreira ◽  
Thiago B. Murari
Keyword(s):  
Supply Chain ◽  
Product Quality ◽  
Automotive Industry ◽  
Industry 4.0 ◽  
Future Outlook ◽  
Control Plan ◽  
Quality Planning ◽  
Planning And Control ◽  
Brazilian Northeast ◽  
And Control

AbstractCOVID-19 outbreak has heavily impacted the manufacturing industry, including Brazilian Automotive Industry. The effects of COVID-19 created restrictions in several industry processes as supply chain. On the other hand, several industry 4.0 technologies is able to support the industry supply chain activities in the COVID 19 scenarios, as well it may contributed for the automotive industry recovery and it will define the next steps of this industry. A supply chain is a network between a company and its suppliers to produce and distribute a specific product to the final buyer. Industry 4.0 is related to the technology development and the digitalization process that improve significantly productivity. Considering the automotive process, an important reference model is described in Advanced Product Quality Planning and Control Plan, that is a manual that communicate the guidelines of the product quality planning and control plan for internal and external suppliers. In this scenario, this paper evaluated the current situation and the future outlook for the adoption of Industry 4.0 technologies in the automotive OEM post-pandemic scenario on the point of view of automotive specialists. The results of this research provide an overview of the current situation and the future outlook for the usage of Industry 4.0 technologies by the Brazilian Northeast automotive OEM, from the perspective of manufacturing engineering experts on APQP.

Sign in / Sign up

Export Citation Format

Share Document