To prepare a material there are four stages where in each stage involved 3 parameters. If it was a single stage and multiple parameters I would ha e used DOE or Taguchi's technique for optimization. What do I do in the case of multiple stages ?
Hi,
Are you looking something in lines of this ideology (Multi-Stage And Multi-Response Process Optimization In Taguchi Method):
https://www.ajol.info/index.php/zj/article/download/142180/131918
B.R.,
Ari
A particular type of manufacturing cannot be simply written up, without knowing the set-up of the machines, their capacities, and so on. Is it a flexible job-shop, or any other standard type of system? More information is needed.
Refer the link:
Article Multiresponse Optimization of Abrasive Water Jet Cutting Pro...
It is a simple fact that there need to be more details explained. The explanation sofar is too vague.
Dear Murali,
you can use grey relational analysis and topsis analysis.
Also, you can refer : Article Effect of Calcium Hexaboride Particles on Predicting the Dry...
Dear Murali,
To solve this problem, we used methods of discrete mathematics – graphs and network models, as well as algorithms for optimization of network models: Dijkstra, Bellman-Ford algorithm. The software developed by the authors of the article was used to automate the process of finding the optimal solution. The use of graphs and network models allows to present in a clear and compact form information about possible technological schemes in production, as well as to systematize the data. The developed program allows to increase the dimension of tasks.
The idea is the following – all possible options for the fields development can be represented in the form of an ordered structure – a graph (eg 37 vertex).
Each vertex (1–37) corresponds to a separate decision (alternative) that can be made, and the distance between the vertices (edge) has its length, which corresponds to the value of the parameter to be optimized (cost, labor, time costs, etc.). The model is structured in stages (levels), i.e. peaks (2–4) may correspond to alternative exploration options, (5–10) possible exploration options, (11–13) possible development technologies, etc. It should be noted that in the presented graph (Fig. 1), the vertices are interconnected according to real relationships, i.e., vertex 1 corresponds to the beginning of the process, vertices 2–4 of the exploration field, the process of exploration begins with the vertex 1 can be connected to vertices 2-4. After that we analyze the network model at each stage, if we have selected vertex 2, then there are two variants of development (vertices 5, 6) and so on. There are two conditions, if there is a connection between the stages of the field development, then the vertices connect, and if not – do not connect. For example, there is a route passing through points 1-3-8-11-16, as well as an alternative route passing through points 1-12-16, i.e. in the first stage of the field development there is a possibility of incomplete exploration of the field. That is, the field development occurs at once, but subsequently due to the lack of an adequate strategy, the development of the field is stopped. In order to find the best strategy, it is necessary to analyze all the steps, that is, to find the shortest route from vertex 1 to vertex 37.
Thus, in order to find the optimal strategy for the field development, all possible options should be presented in the form of an ordered structure – a graph. Then you should set the value of the optimization parameter (in our case, the cost of conducting each stage of field development) as the distance between the vertices of the graph. The totality of vertices that correspond to the stages and distances between the vertices that correspond to the value of the optimization parameter form a network model. The Bellman-Ford algorithm should be used to find the shortest route. The logic is that the process of finding the optimal solution can be carried out, both in the direct order from vertex 1 to 37, and, as a rule, in the opposite direction from vertex 37 to 1. For example, if the task is to design the most cost-effective production, then the opposite should be applied the order in which the field owner wants to reduce the production costs. And if the task is to minimize the adverse impact on the environment, it is better to set a straightforward order (from 1 to 37), when it is necessary to consider additional steps in the form of duilding of additional concentrating factories, etc. Depending on the order of consideration of the model, both environmental and economic options for field development can be analyzed.
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Best regards