An intelligent data mining technique for product quality improvement

Advances in data mining have provided techniques for automatically discovering underlying knowledge and extracting useful information from large volumes of data. Data mining offers tools for quick discovery of relationships, patterns and knowledge in large complex databases. Application of data mining to manufacturing is relatively limited mainly because of complexity of manufacturing data. Growing self organizing map (GSOM) algorithm has been proven to be an efficient algorithm to analyze unsupervised DNA data. However, it produced unsatisfactory clustering when used on some large manufacturing data. In this paper a data mining methodology has been proposed using a GSOM tool which was developed using a modified GSOM algorithm. The proposed method is used to generate clusters for good and faulty products from a manufacturing dataset. The clustering quality (CQ) measure proposed in the paper is used to evaluate the performance of the cluster maps. The paper also proposed an automatic identification of variables to find the most probable causative factor(s) that discriminate between good and faulty product by quickly examining the historical manufacturing data. The proposed method offers the manufacturers to smoothen the production flow and improve the quality of the products. Simulation results on small and large manufacturing data show the effectiveness of the proposed method.

Managing product quality and reliability under new challenges

This paper presents the findings of an investigation of the challenges Australian manufacturers are currently facing. A comprehensive questionnaire survey was conducted among leading Australian manufacturers. This paper reports the main findings of this study. Evidence indicates that product quality and reliability (Q & R) are the main challenges for Australian manufacturers. Design capability and time to market came second. Results show that there is no effective information exchange between the parties involved in production and quality control. Learning from the past mistakes is not proving to have significant effects on improving product quality. The technological innovation speed is high and companies are introducing as many as 5 new products in a year. This technological speed has pressure on the Q & R of new products. To overcome the new challenges, companies need a Q & R improvement model.

Farm-raised shrimp: good aquacultural practices for product quality and safety

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Use of oxygen sensors for the non destructive measurement of oxygen in packaged food and beverage products and its impact on product quality and shelf life

The principal objective of this thesis was to investigate the ability of reversible optical O2 sensors to be incorporated into food/beverage packaging systems to continuously monitor O2 levels in a non-destructive manner immediately postpackaging and over time. Residual levels of O2 present in packs can negatively affect product quality and subsequently, product shelf-life, especially for O2-sensitive foods/beverages. Therefore, the ability of O2 sensors to continuously monitor O2 levels present within food/beverage packages was considered commercially relevant in terms of identifying the consequences of residual O2 on product safety and quality over time. Research commenced with the development of a novel range of O2 sensors based on phosphorescent platinum and palladium octaethylporphyrin-ketones (OEPk) in nano-porous high density polyethylene (HDPE), polypropylene (PP) polytetrafluoroethylene (PTFE) polymer supports. Sensors were calibrated over a temperature range of -10°C to +40°C and deemed suitable for food and beverage packaging applications. This sensor technology was used and demonstrated itself effective in determining failures in packaging containment. This was clearly demonstrated in the packaging of cheese string products. The sensor technology was also assessed across a wide range of packaged products; beer, ready-to-eat salad products, bread and convenience-style, muscle-based processed food products. The O2 sensor technology performed extremely well within all packaging systems. The sensor technology adequately detected O2 levels in; beer bottles prior to and following pasteurisation, modified atmosphere (MA) packs of ready-to-eat salad packs as respiration progressed during product storage and MA packs of bread and convenience-style muscle-based products as mycological growth occurred in food packs over time in the presence and absence of ethanol emitters. The use of the technology, in conjunction with standard food quality assessment techniques, showed remarkable usefulness in determining the impact of actual levels of O2 on specific quality attributes. The O2 sensing probe was modified, miniaturised and automated to screen for the determination of total aerobic viable counts (TVC) in several fish species samples. The test showed good correlation with conventional TVC test (ISO:4833:2003), analytical performance and ruggedness with respect to variation of key assay parameters (probe concentration and pipetting volume). Overall, the respirometric fish TVC test was simple to use, possessed a dynamic microbial range (104-107 cfu/g sample), had an accuracy of +/- one log(cfu/g sample) and was rapid. Its ability to assess highly perishable products such as fish for total microbial growth in <12 hr demonstrates commercial potential.

Product quality judgments in a two-sequence cue environment

Previous research demonstrated that the sequence of informational cues and the level of distraction have an impact on the judgment of a product’s quality. This study investigates the influence of the force behind the processing of these cues, working memory (WM). The results indicate that without distraction, consumers with low and high WM capacity (WMC) equally base their product evaluation on the first sequential cue. In the presence of a distractor, however, low WM individuals are no longer able to recall the initial cue, and thus derive their product judgment from the final cue. Moreover, evidence of intercultural differences in the perception of product related cues, and their aptitude for signaling a favorable product quality is provided.

Impact of Product Quality, Service Quality and Contextual Experience on Customer Perceived Value and Future Buying Intentions

Recognizing that high satisfaction leads to high customer loyalty, companies today are aiming for total customer satisfaction. This article explains relative impact of product quality, service quality and contextual experience on customer perceived value and intention to shop in the future. The data has been collected using a questionnaire from 205 customers of a national retailer chain. The relative importance of product quality, service quality and contextual experience on customer perceived value and thus on customer preference and future intentions was measured using multiple regression. Also, the contribution of perceived value to preference and thus on future buying intention was also measured. Structural Equation Model (SEM) using Amos 4 was used to find the overall fitness of the model. It was found that product quality, service quality and contextual experience have a major influence on customer perceived value

Consumer choice, information product quality, and market implications

The paper concerns with the peculiarities of consumer choice in information product markets. This is a multidisciplinary study based on both information system research and microeconomic theory. An extension is introduced to the conventional general theory of consumer choice for explicitly taking into account the impact of information product quality on consumer behaviour. Multiple quality characteristics, considered against the price of product, are an essential reason for consumer choice of high tech product in general and information product in particular. We assume that consumers are able to aggregate their preferences of multiple product characteristics into a product preference order. On the supply side, the product quality characteristics incur costs. In the case of information product, those costs are the costs of the first copy, and marginal costs are near zero. All of the above constitute the distinctive characteristics of the competitive mechanism in the digital economy and in information product markets. A model, based on the game theory is used to consider two special cases. The first one deals with monopolistic competition for a share of the market with a limited number of customers. Conditions are derived for IT firm survival. The second one considers conditions at which a monopoly is able to successfully introduce a new version if its information product.

Growth and product quality of European eel (Anguilla anguilla) as affected by dietary protein and lipid sources

A 12-week feeding trial was undertaken to evaluate the effects of partial replacement of marine raw materials in the diet with soybean meal and beef tallow on growth and product quality of European eel (Anguilla anguilla ). Based on growth, feed efficiency and chemical composition, soybean meal was found to be an unsuitable ingredient for eel diets as a substitute for fishmeal (25% on a protein basis), probably because of the low digestibility of its carbohydrate content. However, beef tallow can be used to replace 50% of fish oil without reduction in growth, provided that digestible carbohydrates are present in the diet. No major effects of protein and lipid sources in the diet were found on fillet chemical composition. Sensory analysis revealed no significant differences between fish fed the control and the experimental diets, with the exception of salty taste which was significantly higher in fish fed combined soybean meal and beef tallow compared with fish fed the control diet.