Carlos J. Perez-Gonzalez

The impact of overdispersion on the design of optimal reliability demonstration test plans for beta-binomial models with Weibull, gamma, and lognormal lifetime distributions is analyzed. Assuming limited producer and consumer risks, fixed-duration test plans with minimal sample sizes and optimal-duration test plans with minimum costs based on failure count data are determined by solving the corresponding nonlinear programming problems when the fluctuation of the failure probability is described by a beta distribution. If the test time is fixed, the overdispersion effect on the optimal sample size and decision criterion is important in most situations. The influence is less relevant when the engineer also wants to find the minimum-cost test time. Optimal-duration plans usually outperform fixed-duration schemes in terms of costs and robustness against overdispersion. The use of lot inspection schemes with optimal reliability test times is strongly recommended when the presence of overdispersed failure count data is suspected. Applications of the developed methodology to the manufacturing of microelectronic chips and semiconductor lasers are provided for illustrative and comparative purposes.

Repetitive group inspection of production lots is considered to develop the failure censored plan with minimal expected sampling effort using prior information. Optimal reliability test plans are derived for the family of log-location-scale lifetime distributions, whereas a limited beta distribution is assumed to model the proportion nonconforming, p. A highly efficient and quick step-by-step algorithm is proposed to solve the underlying mixed nonlinear programming problem. Conventional repetitive group plans are often very effective in reducing the average sample number with respect to other inspection schemes, but sample sizes may increase under certain conditions such as high censoring. The inclusion of previous knowledge from past empirical results contributes to drastically reduce the amount of sampling required in life testing. Moreover, the use of expected sampling risks significantly improves the assessment of the actual producer and consumer sampling risks. Several tables and figures are presented to analyse the effect of the available prior evidence about p. The results show that the proposed lot inspection scheme clearly outperforms the standard repetitive group plans obtained under the traditional approach based on conventional risks. Finally, an application to the manufacture of integrated circuits is included for illustrative purposes.

Companies face the challenge of managing customer relationships (CRM) in a context marked by a drastic digital transformation and unbridled evolution of consumer behavior, exacerbated by the COVID-19 pandemic. The customer is more demanding, has access to the global market and interacts with companies through multiple digital channels, such as email, social networks, mobile apps or instant messaging. In this situation, the success of a CRM implementation highly depends on information technology and the applications used. To harmonize this new business context with the development of information systems (IS), a suitable CRM ontology and enterprise architecture (EA) is needed. While an ontology-based conceptual model provides a unifying framework, aids sharing and reusing knowledge, and facilitates communication within a domain, an EA-based model unequivocally describes, analyzes, and visualizes how an organization should operate from the perspective of business, application, and technology. The purpose of the paper is the proposal of CURIE-O, a CRM OntoUML UFO-based ontology, together with CURIE-EA, a CRM ArchiMate-based EA to serve business managers and IS specialists an updated unifying framework of reference in the CRM domain as well as a highly efficient tool to support application development and maintenance in this changing and increasingly digital context. Modeling has proven to be an essential element to achieve high-performance information systems. In order to apply the ontology and the EA proposed here, the authors developed a CRM task management application prototype that was implemented as a case study in a consulting company. The methodology followed was design science research (DSR), in order to design and validate the artifacts. Within the DSR framework, other complementary research methods have been used, in particular literature research, interviews and focus groups carried out with several hotel chains in Tenerife (Canary Islands). The main existing CRM models in the scientific literature have also been analyzed together with the leading CRM market solutions.

The construction of prediction sets (or regions) for future failure times based on a type-II censored sample from the exponential distribution is investigated. Based on the distribution of the sum of independent exponential variables with different parameters, we obtain the distribution of the required pivotal quantities in order to find the prediction regions. Balanced prediction sets are first derived. A constrained optimization problem is then formulated and solved to determine the prediction region with minimal area. A Monte Carlo simulation study is carried out to compare the performance of the proposed prediction sets. Two real data examples are provided and analyzed to illustrate the methods presented. Finally, some applications and extensions of the results are discussed.

Echolocating animals that forage in social groups can potentially benefit from eavesdropping on other group members, cooperative foraging or social defence, but may also face problems of acoustic interference and intra-group competition for prey. Here, we investigate these potential trade-offs of sociality for extreme deep-diving Blainville′s and Cuvier's beaked whales. These species perform highly synchronous group dives as a presumed predator-avoidance behaviour, but the benefits and costs of this on foraging have not been investigated. We show that group members could hear their companions for a median of at least 91% of the vocal foraging phase of their dives. This enables whales to coordinate their mean travel direction despite differing individual headings as they pursue prey on a minute-by-minute basis. While beaked whales coordinate their echolocation-based foraging periods tightly, individual click and buzz rates are both independent of the number of whales in the group. Thus, their foraging performance is not affected by intra-group competition or interference from group members, and they do not seem to capitalize directly on eavesdropping on the echoes produced by the echolocation clicks of their companions. We conclude that the close diving and vocal synchronization of beaked whale groups that quantitatively reduces predation risk has little impact on foraging performance.