Concept for Robot-Based Cable Assembly Regarding Industrial Production

The assembly of cables in industrial production is still a largely manually performed task. Therefore, automatic cable assembly offers much potential in terms of efficiency. The major challenge of automating this task lies in the formlessness of the cables, which entails unknown and inconstant states of the assembly objects. In this paper, a process chain and a concept are presented for the automated cable assembly in an industrial context. The process chain consists of five process steps, which are used to structure existing approaches and system configurations for automated cable assembly from a production technology perspective. The emphasis is on the coverage of the process steps and the system technology. The presented concept represents an approach for robotic cable assembly focusing on the flexibility to process multiple product variants. Basis for the ability to handle a variety of variants is the avoidance of a forced shape on the cables. For this approach, system technology as well as challenges and possible solutions are presented.

Prevalence and characteristics of ever regular use of non-combustible nicotine for 1 year or more: a population survey in England

Introduction Up-to-date monitoring of non-combustible nicotine products (e.g. e-cigarettes, nicotine replacement therapies (NRT), heated tobacco products (HTP); NNP) is important to assess their impact. To date, there is little evidence on the association between ever regular use (defined here as 1 year or more) of NNP and current smoking status. Aims/methods The purpose of this study was to examine the prevalence, and sociodemographic, alcohol and smoking status correlates, of ever regular use of NNP in England in 2020. A cross-sectional survey of adults in England was conducted between February and June 2020. Results A total of 8486 adults were surveyed; 94.9% (8055) were complete cases. The weighted prevalence of ever regular NNP use was 5.4% (n = 436; 95% CI 5.0–6.0), of which 82% (n = 360; 95% CI 78.7–85.8) was single and 18% (n = 79; 95% CI 14.8–22) multiple product use. Amongst ever regular NNP users, the prevalence of ever regular NRT, e-cigarette and HTP use was 64.7% (95% CI 60.1–69), 43.4% (95% CI 38.8–48) and 2.5% (95% CI 1.4–4.5), respectively. In adjusted analysis, ever regular NNP use was associated with smoking status, being significantly higher among current (22.3%; adjusted OR (aOR) 34.9, 95% CI 24.0–50.8) and ex-smokers (12.7%, aOR 19.8, 95% CI 11.1–14.4) than among never-smokers (0.6%). More advantaged occupational grade (aOR, 1.27 95% CI 1.02–1.57) and at least hazardous alcohol use (aOR, 1.38 95% CI 1.06–1.78) were associated with greater prevalence of ever regular NNP use. Conclusions Ever regularly using NNP was highest among smokers and ex-smokers and rare among never-smokers. Among people who have ever regularly used NNP, NRT is the most popular.

“Worse Than What I Read?” The External Effect of Review Ratings on the Online Review Generation Process: An Empirical Analysis of Multiple Product Categories Using Amazon.com Review Data

In this paper, we study the online consumer review generation process by analyzing 37.12 million online reviews across nineteen product categories obtained from Amazon.com. This study revealed that the discrepancy between ratings by others and consumers’ post-purchasing evaluations significantly influenced both the valence and quantity of the reviews that consumers generated. Specifically, a negative discrepancy (‘worse than what I read’) significantly accelerates consumers to write negative reviews (19/19 categories supported), while a positive discrepancy (‘better than what I read’) accelerates consumers to write positive reviews (16/19 categories supported). This implies that others’ ratings play an important role in influencing the review generation process by consumers. More interestingly, we found that this discrepancy significantly influences consumers’ neutral review generation, which is known to amplify the effect of positive or negative reviews by affecting consumers’ search behavior or the credibility of the information. However, this effect is asymmetric. While negative discrepancies lead consumers to write more neutral reviews, positive discrepancies help reduce neutral review generation. Furthermore, our findings provide important implications for marketers who tend to generate fake reviews or selectively generate reviews favorable to their products to increase sales. Doing so may backfire on firms because negative discrepancies can accelerate the generation of objective or negative reviews.