A demerit-fuzzy rating system,monitoring scheme and classification for manufacturing processes

For monitoring online manufacturing processes, the proportion of weights imposed on each type of product’s defects (nonconformities or demerits) has a profoundly effective impact on control charts’ performance. Apparently, the demerit-chart approach is superior than the widely-used c-chart scheme, because it allows us to place relative precise weights (real numbers) on defects according to their distinctly inferior degrees affecting the product quality so that the abnormal variations of processes can be literally exposed. However, in many applications, the seriousness of defects is evaluated partially or entirely by the inspectors’ perceptive judgement or knowledge, so with the precise-weight assignment, the demerit rating mechanism is considered to be somewhat constrained and subjective which inevitably leads to the targeted manufacturing process with limited and possibly biased information for online surveillance. To cope with the drawback, a demerit-fuzzy rating system and monitoring scheme is proposed in this paper. We first incorporate fuzzy weights (fuzzy numbers) to properly reflect the severity measures of defects which are categorized linguistically. Then, based on properties of fuzzy set theory and proposed approaches for fuzzy-number ranking, we develop the demerit-fuzzy charting scheme which is capable of discriminating process conditions into multi-intermittent statuses between in-control and out-of-control. This approach improves the traditional process control techniques with the binary-classification restraint for the process conditions. Finally, the proposed demerit-fuzzy rating system, monitoring scheme, and classification is elucidated by an application in garment industry to monitor textile-stitching nonconformities conditions.     

Novel associative classifier based on dynamic adaptive PSO: Application to determining candidates for thoracic surgery

Association rule mining is a data mining technique for discovering useful and novel patterns or relationships from databases. These rules are simple to infer and intuitive and can be easily used for classification in any domain that requires explanation for and investigation into how the classification works. Examples of such areas are medicine, agriculture, education, etc. For such a system to find wide adoptability, it should give output that is correct and comprehensible. The amount of data has been growing very fast and so has the search space of these problems. So we need to change traditional methods. This paper discusses a rule mining classifier called DA-AC (dynamic adaptive-associative classifier) which is based on a Dynamic Particle Swarm Optimizer. Due to its seeding method, exemplar selection, adaptive parameters, dynamic reconstruction of regions and velocity update, it avoids premature convergence and provides a better value in every dimension. Quality evaluation is done both for individual rules as well as entire rulesets. Experiments were conducted over fifteen benchmark datasets to evaluate performance of proposed algorithm in comparison with six other state-of-the-art non associative classifiers and eight associative classifiers. Results demonstrate competitive performance of proposed DA-AC while considering predictive accuracy and number of mined patterns as parameters. The method was then applied to predict life expectancy of post operative thoracic surgery patients.     

Effect of extraction systems on the quality of virgin olive oil

Research has been carried out to ascertai the effects of different processing systems on olive oil quality. Tests were performed in industrial oil mills that were equipped with both pressure and centrifugation systems. Results show that oils extracted from good-quality olives do not differ in free fatty acids, peroxide value, ultraviolet absorption and organoleptic properties. Polyphenols ando-diphenols contents and induction times are higher in oils obtained from good-quality olives by the pressure system because it does not require addition of water to the olive paste. The centrifugation system requires the addition of warm water to the olive paste and helps to obtain oils with a lower content of natural antioxidants. Oils obtained from poorquality or from ripe olives in continuous centrifugal plants are lower in free fatty acids than those obtained by the pressure system. Dr. Mario Solinas is deceased—May 23, 1993.     

用预分解技术改造Φ4×60m预热器窑的又一成功实例

介绍南京水泥工业设计研究院用预分解生产技术对山东水泥厂Φ4×60m预热器窑烧成系统进行的成功技术改造。技改设计指标为：熟料产量保证指标1500t／d，争取指标1700t／d，熟料热耗＜3762kJ／kg，熟料28d抗压强度＞60MPa。整个工程停产施工耗时仅用48d，烧成系统技改共耗资约3000万元。技改后一次点火投料成功，且点火当月即实现72h达标考核，所有设计指标均达标。     

Detection of beeswax adulterations using concentration guide‐values

The concentrations of 102 chemical compounds (saturated and unsaturated hydrocarbons, palmitates, total and free acids, total hydroxyacids, total and free alcohols, acidic monoesters and monoesterified 1,2,3‐propanetriols) have been determined by GC/FID on white and yellow comb beeswax of Apis mellifera from different regions of Spain. Guide‐value ranges are proposed for its characterization and to discriminate adulterated foundation beeswax sheets. The concentrations of many compounds resulted to be statistically different for white and yellow beeswaxes, while the observation of concentrations out of normal in some marketed foundation beeswax sheets suggested their adulteration. However, the measurement of anomalous concentrations in foundation beeswax sheets did not imply necessarily their rejection by the bees.     

如何提高预焙铝电解槽阳极质量

预焙阳极的质量已严重制约铝电解技术的发展，必须予以足够的重视．国外在提高阳极质量方面的有效措施，可以供国内阳极工厂技术改造及科研攻关借鉴．     

纳米材料在涂料中的应用

简述了纳米微粒的基本性质，介绍了几种典型的功能纳米材料在涂料中的应用．并探究其对涂料的改性原理．对应用中存在的问题进行了剖析。     

修复土壤,腐植酸能做些什么

我国土壤污染形势严峻,已成为农产品安全和农业可持续发展的一大障碍."十一五"期间已将防治土壤污染列入重要议事日程,"全国土壤污染状况调查和防治项目"业已启动,2006年11月<农产品质量安全法>也开始实施.腐植酸学术界及行业又面临新的机遇和挑战.介绍了我国土壤污染的现状及其治理技术,阐述了腐植酸类物质(HS)修复污染土壤的研究进展、存在问题及应用的可行性,并对今后的研究开发及应用方向提出若干建议.     

海绵钛的生产及应用

介绍了海绵钛的主要特点、用途、质量及生产方法。