Identification of concurrent control chart patterns with singular spectrum analysis and learning vector quantization

Identification of unnatural control chart patterns (CCPs) from manufacturing process measurements is a critical task in quality control as these patterns indicate that the manufacturing process is out-of-control. Recently, there have been numerous efforts in developing pattern recognition and classification methods based on artificial neural network to automatically recognize unnatural patterns. Most of them assume that a single type of unnatural pattern exists in process data. Due to this restrictive assumption, severe performance degradations are observed in these methods when unnatural concurrent CCPs present in process data. To address this problem, this paper proposes a novel approach based on singular spectrum analysis (SSA) and learning vector quantization network to identify concurrent CCPs. The main advantage of the proposed method is that it can be applied to the identification of concurrent CCPs in univariate manufacturing processes. Moreover, there are no permutation and scaling ambiguities in the CCPs recovered by the SSA. These desirable features make the proposed algorithm an attractive alternative for the identification of concurrent CCPs. Computer simulations and a real application for aluminium smelting processes confirm the superior performance of proposed algorithm for sets of typical concurrent CCPs.

Business ethics in TQM : the qualities and spectrum zones of a case illustration

Purpose - The objective of this research is to introduce and describe a conceptual framework of business ethics in TQM.

Design/methodology/approach - In order to highlight the concepts proffered, a case study in the Swedish retail industry was conducted. The data that underpin the case illustration have been collected as part of a larger research project in the Swedish retail industry. Draws on and reports the findings from one case of the larger research project that has been used in this instance to inform the role of business ethics in TQM. The case illustration is based on a qualitative approach. The data were collected through interviews with leading executives in the corporation,

Findings - Both time and context become crucial parameters to manage the quality and spectrum zones of core values in the marketplace. In fact, the necessary quality management of business operations has to be performed without delay, minimising the damage. Therefore, the importance of business ethics becomes evident in TQM. In the long run, TQM will not succeed in business operations unless business ethics is considered in the core values to support the techniques and tools applied.

Research limitations/implications - The model has only been tested by relating it to one case in the Swedish retail industry.

Practical implications - TQM is dependent on the contextual and evolutionary issues in the marketplace. Therefore, TQM should be interpreted as a continuous process. The importance of continuously monitoring the spectrum zones and qualities of core values in TQM should not be under-estimated. Therefore, business ethics should always be present in TQM. Further research would benefit from other case studies of how business ethics benefits TQM. Therefore, the dynamics of business ethics in TQM should be further explored.

Originality/value - Business ethics needs to be an essential consideration of any TQM process. Examines how an organization can incorporate this task.

Autism spectrum disorder symptoms in children with ADHD: a community-based study

This study examined the prevalence of autism spectrum disorder (ASD) symptoms in a community-based sample of children with attention-deficit/hyperactivity disorder (ADHD) and non-ADHD controls. We also examined the relationship between ASD symptoms and ADHD subtype, ADHD symptom severity and child gender. Participants were 6-10-year-old children (164 ADHD; 198 non-ADHD control) attending 43 schools in Melbourne, Australia, who were participating in the Children's Attention Project. ADHD was assessed in two stages using the parent and teacher Conners' 3 ADHD index and the Diagnostic Interview Schedule for Children IV (DISC-IV). ASD symptoms were identified using the Social Communication Questionnaire (SCQ). Unadjusted and adjusted linear and logistic regression examined continuous and categorical outcomes, respectively. Children with ADHD had more ASD symptoms than non-ADHD controls (adjusted mean difference=4.0, 95% confidence interval (CI) 2.8; 5.3, p<0.001, effect size=0.7). Boys with ADHD had greater ASD symptom severity than girls with ADHD (adjusted mean difference=2.9, 95% CI 0.8; 5.2, p=0.01, effect size=0.4). Greater ADHD symptom severity was associated with greater ASD symptom severity (regression co-efficient=1.6, 95% CI 1.2; 2.0, p<0.001). No differences were observed by ADHD subtype. Greater hyperactive/impulsive symptoms were associated with greater ASD symptoms (regression coefficient=1.0; 95% CI 0.0; 2.0, p=0.04) however, this finding attenuated in adjusted analyses (p=0.45). ASD symptoms are common in children with ADHD. It is important for clinicians to assess for ASD symptoms to ensure appropriate intervention.