Eclectic Method for Developing Optimum ANN´s

Today one of the biggest problems found in developing and implementing Artificial Neural Networks (ANN) is the lack of a rigorous methodology that ensures the development of optimum ANN, because the performance of their function is measured by trial and error, leading to loss of time in training networks that are far away to reach the expected error rate and adequate performance. As a part of the investigation, a method for determining the optimal networks for prediction and function approximation networks with more than one output is proposed and developed. However, steps can be implemented in hard systems methodologies to analyze the characteristics of the variables required for training the ANN and the correlation between them to reduce the optimal search time. A methodology for the construction and development of an ANN is proposed and developed based on Checkland, Jenkins and Hall methodologies, obtaining a 14-step methodology grouped into three stages

A multi-criteria framework for Supplier Quality Development

Supplier Development (SD) includes efforts undertaken by firms to improve their suppliers’ capabilities and performance. It has emerged as one of the leading business practices in the past few years. Development of supplier’s quality is an important part of these programs. Supplier Quality Development Programs (SQDPs) are strategic quality development activities for increasing quality, reliability and efficiency of suppliers. Evaluation and selection of appropriate SQDPs to improve quality of supply chain is target of most companies, but results of these evaluations cannot be validated without ensuring credibility of a set of criteria. These criteria are factors that ensure success of SQD activities and used for ranking these efforts. In this thesis, we propose a multi-criteria framework for Supplier Quality Development integrating DMAIC principles. In the Define phase, we identify criteria for SQD using systematic review of literature and industrial practices. In the Measure phase, we conduct a survey study with supply chain quality experts to measure the importance of SQD criteria. In the Analyze phase, we classify the SQD criteria into three groups using Kano’s model by analyzing them from the perspective of fulfilling basic needs, performance needs, and delighters/exciters. To examine the relationship between various SQD criteria, we apply Interpretive Structural Modeling (ISM) technique. In the improve phase, we apply the selected criteria to evaluate various Supplier Quality Development Programs using Multi-Criteria Analysis (MCA) technique called TOPSIS ( Technique for Order of Preference by Similarity to Ideal Solution) and select the best one. In the control phase, we suggest audits for ensuring the criteria used for evaluation are up-to-date with the latest practices. The strength of the proposed work is a comprehensive investigation of SQD criteria using knowledge from quality experts, literature review and industrial practice and suggestion of a practical multi-criteria analysis framework for evaluation and selection of appropriate SQDPs