Jianjun Yu

Green Scheduling and its Solution

Production scheduling is the key for the enterprise efficiency improvement, and is hot research topic for the advanced manufacturing all the time. Green manufacturing has become the inevitable trend, but environmental protection is ignored in scheduling research and in fact it’s very important. The concept of green scheduling is put forward and the definition of green scheduling is present. The difference between green scheduling and traditional scheduling is contrasted. The environmental effect and the resource consumption are synthetically taken into account, accordingly the index system of green scheduling is constructed and the model of green scheduling is set up. The resolution strategy with two steps is put forward for green scheduling. Pareto optimal solution set is firstly obtained, and then Pareto optimal solutions are evaluated and determined with the standardization and the entropy weight, and the satisfying solution is finally searched out.

Customer-Value-Based Order Acceptance Policy in Make-to-Order Manufacturing

Creation and sustenance of long-term relationships with their customers is a key success factor in make-to-order manufacturing firms. In order to achieve both maximum cumulative profit and long-term profitable customer relationships, we integrate customer value into order acceptance decision. Then we use linear programming to model the order acceptance problem, and solve it with reinforcement learning approach. The results of simulation show that the proposed policy can achieve both maximum cumulative profit and long-term profitable customer relationships. An intelligent decision policy to control the coming orders is learned by the agent.

Due Date Model Build and Analysis Based on Multi-Vendors

The due date set is affected by the coordination and cooperation between enterprise and customers and due date requirement and sensitivity degreed of different types of customers are different. In order to analyze more complex situations, the problem and its model including two vendors, one manufacturers and consumers is studied in the paper. Firstly, the model is built and analyzed in view of the vendors, and the optimal due date is obtained after calculation. The analysis results show that there is not any relationship between the order function and the demand quantity, the demand quantity does not affect the order period. Secondly, the model is built and analyzed in view of the manufacturer, and the optimal due date is obtained after calculation, and the inventory cost coefficient is calculated. The analysis results show that the inventory cost arising from delay in delivery is actually proportional function about the overall demand for A. Finally, the model is built and analyzed in view of the coordination between the manufacturer and the vendors, and the optimal due date is obtained after calculation, and the maximum of whole supply chain profit is calculated. According to the benefit analysis, the whole profit is indeed bigger than separate operation.

Analysis of Industrial Engineering in South China University of Technology

South China University of Technology performs some new experiments in industrial engineering education and obtains some effectiveness, and these experiences can provide reference for other universities. In the paper, industrial engineering characteristic is introduced, and industrial engineering education is analyzed. Demand analysis and importance evaluation of industrial engineering are performed. Competition ability of industrial engineering is analyzed. Industrial engineering employment data of South China University of Technology are collected, and the reasons for good employment are analyzed. Analysis results show that education innovation can improve industrial engineering of South China University of Technology.

Dynamic Joint Decision on Price and Delivery Date in MTO Manufacturer Based on Agent

In order to maximize the total profit and improve the service level, based on the perspective of queuing theory, a new approach for dynamic joint decision on price and delivery date in Make-to-order (MTO) manufacturing firms using Q-learning algorithm was proposed. Compared with static price and delivery date policy, the simulation results show that the proposed algorithm performs better in total profit and service level. The total profit does not increase with the growing number of accepted orders and the number of accepted orders must match the production capacity.

Tri-Objective Optimization in Production Based on Stochastic Principle

Tri-objective optimization of time, cost and quality is complex and valuable research hotspot which is of expansive practice application foreground. Exact method can only solve some small scale optimization problem, but the practice problem is usually large scale. In order to analyze and research the complex large scale optimization problem, the integrative optimization model of time-cost-quality is set up according to the action rules and relations of three objectives. Tri-population genetic algorithm is put forward for the optimization model based on the idea of intellective stochastic search. The algorithm adopts different populations to carry out the parallel search to realize rapid optimization. Finally the methods put forward are applied to manufacturing case of airplane part, and a series of optimization result is achieved. The case application validates the correctness of the model and the availability of the algorithm.

Exact Optimization of Time, Cost and Quality in Manufacturing

Time, cost and quality are three central objectives the manufacturing enterprises seek, but they restrict and affect each other. To analyze the relations among three objectives and achieve their exact optimization during manufacturing are the important problems which are worth researching. Based on the practice investigation and reasoning, the action mechanisms of three objectives are deeply analyzed, and their effect rules and relations are ascertained. The optimization model of time-cost-quality is set up according to their relations. The special program is designed for the integrative optimization model based on the idea of accurate calculation, and is applied to solve the optimization problem. Finally the methods put forward are applied to the instance about car part manufacturing, and a series of optimization result is obtained. Some conclusions which are valuable for the manager in enterprise are summarized by analyzing the optimization result. The instance application indicates that the model and the methods can help to make decision for production.

Theory of assembly buffer for line balancing problem

Line balancing problem is the bottleneck of flow production. How to adjust the line to decrease the pressure of bottleneck workstations and reduce the mistake rate is the frequent focus in production. In the paper, Theory of Assembly Buffer (TAB) is put forward to design rhythm of assembly lines, and workers tension degree model is built. Dynamic and multi-time rhythm adjustment of line balancing is achieved. The instance application proves that the methods put forward can effectively eliminate the negative impacts of bottleneck operation on the stability of successive flow among workstations.