Tatjana Sibalija

An integrated approach to optimise parameter design of multi-response processes based on Taguchi method and artificial intelligence

The Taguchi robust parameter design has been widely used over the past decade to solve many single-response process parameter designs. However, the Taguchi method is unable to deal with multi-response problems that are of main interest today, owing to increasing complexity of manufacturing processes and products. Several recent studies have been conducted in order to solve this problem. But, they did not effectively treat situations where responses are correlated and situations in which control factors have continuous values. This study proposed an integrated model for experimental design of processes with multiple correlated responses, composed of three stages which (1) use expert system, designed for selecting an inner and an outer orthogonal array, to design an actual experiment, (2) use Taguchi’s quality loss function to present relative significance of responses, and multivariate statistical methods to uncorrelate and synthesise responses into a single performance measure, (3) use neural networks to construct the response function model and genetic algorithms to optimise parameter design. The effectiveness of the proposed model is illustrated with three examples. Results of analysis showed that the proposed approach could yield a better solution in terms of the optimal parameters setting that results in a higher process performance measure than the traditional experimental design.

An intelligent approach to robust multi-response process design

In order to meet strict customer demands in a global highly-complex industrial sector, it is necessary to design manufacturing processes based on a clear understanding of the customers requirements and usage of a product, by translating this knowledge into the process parameter design. This paper presents an integrative, general and intelligent approach to the multi-response process design, based on Taguchis method, multivariate statistical methods and artificial intelligence techniques. The proposed model considers process design in a general case where analytical relations and interdependency in a process are unknown, thus making it applicable to various types of processes, and incorporates customer demands for several (possible correlated) characteristics of a product. The implementation of the suggested approach is presented on a study that discusses the design of a thermosonic copper wire bonding process in the semiconductor industry, for assembly of microelectronic devices used in automotive applications. The results confirm the effectiveness of the approach in the presence of different types of correlated product quality characteristics.

The Measurement System Analysis as a Performance Improvement Catalyst:A Case Study

The capability to manage and control the Business Performances (BPs) of a company is nowadays a leveraging factor for the own competitiveness. One of the most important factors to improve business performance indicators is the development of a structured Quality Management system. Among a plethora of various methodologies, Six Sigma is one of the most important methodologies to improve product and process quality, reduce wastes and costs and achieve higher efficiency and effectiveness, strongly influencing the performance indicators of manufacturing companies. The Six Sigma measurement phase in the DMAIC sequence, as well as all kinds of the measurement activities, should be strictly controlled in terms of effectiveness, precision, variation from the actual values, etc. In respecting these restrictive requirements, the Measurement System Analysis (MSA) is becoming necessary to evaluate the test method, measuring instruments, and the entire process of obtaining measurements in order to ensure the integrity of data used for analysis and to understand the implications of measurement error for decisions making about a product or process. The article presents the MSA action implemented in a manufacturing company, as a case study. Preliminary qualitative and quantitative analysis follow and the main result are presented. The measurement system capability is analyzed. The MSA action strongly influences the company’s general business performance as revealed by the final analysis in the article.

Impact analysis of the implemented quality management system on business performances in pharmaceutical-chemical industry in Serbia

International quality management standard (QMS) ISO 9001 became widely accepted as a framework for product and/or services quality improvement. There are recent research conducted in order to define relationships and effects between the applied QMS and financial and/or non-financial business parameters. The effects of the applied pharmaceutical quality system (PQS) on the business performances in Serbian pharmaceutical-chemical industry are analyzed in this paper using multivariate linear regression analysis. The empirical data were collected using a survey that was performed among experts from Serbian pharmaceutical-chemical industrial sector during 2010. An extensive questionnaire was used in the survey, grouping the questions in eight groups: Implementation of pharmaceutical quality system (AQ), Quality/strategy planning (QP), Human resource management (HR), Supply management (SM), Customer focus (CF), Process management (PM), Continuous improvement (CI), and Business results (BR). The primary goal of the research was to analyze the effects of the elements of first seven groups (AQ, QP, HR, SM, CF, PM, and CI) that present various aspects of the implementation of PQS, on the elements of business results (BR). Based on empirical data, regression relations were formed to present the effects of all considered elements of PQS implementation on the business performance parameters (BR). The positive effects of PQS implementation on the business performances such as the assessment of performance indicators, continual products and/or services quality improvement, and efficient problem solving, are confirmed in the presented research for the Serbian pharmaceutical-chemical industrial sector. The results of the presented research will create a room for the improvement of the existing models in application, and for attracting interested parties that aim to commence this business standardization process. Hence, implementation of PQS is not only the regulatory requirement or advertising movement, but very important issue for the development and improvement of business performances.