Selecting parameters and limits for equipment operational qualification

While operational qualification (OQ) is a well-established term within equipment qualification, users of equipment often become unsure when it comes to implementation. The biggest problem is how to select procedures and acceptance criteria. Should these be the vendor's specifications or should the users define their own limits, and, if so, how? Should all instruments of the same type have the same values or should these be optimized for each individual instrument? This article will provide an overall strategy and specific examples for HPLC on how to select procedures and acceptance limits that are based on efficient use of resources, on practicality and on the intended use of the equipment.     

Reliability tests for Weibull distribution with variational shape parameter based on sudden death lifetime data

In the traditional design of reliability tests for assuring the mean time to failure (MTTF) in Weibull distribution with shape and scale parameters, it has been assumed that the shape parameter in the acceptable and rejectable populations is the same fixed number. For the purpose of expanding applicability of the reliability testing, Hisada and Arizono have developed a reliability sampling scheme for assuring MTTF in the Weibull distribution under the conditions that shape parameters in the both populations do not necessarily coincide, and are specified as interval values, respectively. Then, their reliability test is designed using the complete lifetime data. In general, the reliability testing based on the complete lifetime data requires the long testing time. As a consequence, the testing cost becomes sometimes expensive. In this paper, for the purpose of an economical plan of the reliability test, we consider the sudden death procedure for assuring MTTF in Weibull distribution with variational shape parameter.     

Monotonicity in the stock competition game with consumer search

Anupindi and Bassok investigate the impact of centralizing the stocks in a one-manufacturer-two-retailer supply chain with consumer search. They observed through numerical studies that in the decentralized scenario, the retailers’ order quantities are monotonic in the consumer search probability. This paper provides an analytical justification of this monotonicity.     

Handling selection bias when choosing actions in retail credit applications

In many situations one needs to know which action one should take with a customer to yield the greatest response. Typically, estimates of the response functions of different actions will be based on the responses of customers previously assigned to each action. Often, however, the previous assignments will not have been random, so that estimates of the response functions will be biased. We examine the case of two possible actions. We look at the error arising from using the simple OLS estimate ignoring the selection bias, and also explore the possibility of using the Heckman model to allow for the sample selectivity. The performance of Heckman’s model is then compared with the simple OLS through simulation.     

Structural models in consumer credit

We propose a structural credit risk model for consumer lending using option theory and the concept of the value of the consumer’s reputation. Using Brazilian empirical data and a credit bureau score as proxy for creditworthiness we compare a number of alternative models before suggesting one that leads to a simple analytical solution for the probability of default. We apply the proposed model to portfolios of consumer loans introducing a factor to account for the mean influence of systemic economic factors on individuals. This results in a hybrid structural-reduced-form model. And comparisons are made with the Basel II approach. Our conclusions partially support that approach for modelling the credit risk of portfolios of retail credit.     

The use of uncertainty estimates of test results in comparisons with acceptance limits

When a test is performed in order to qualify a material or a product for a certain use, the result is generally compared with an acceptance limit. The test result has an uncertainty which should be estimated and stated (e.g. in accordance with GUM). Very often this is not the case. Further, discussions often arise on the issue of how the uncertainty shall be considered in relationship to the acceptance limit. The intention of this note is to describe, in simple terms, the statistical background and to give some recommendations. In short, there are two clean-cut, extreme situations. The first case is when the uncertainty of the testing procedure is the dominating factor. Here it is found that the estimates of single laboratories cannot, generally, be used for comparisons with acceptance limits. One should have standardised, well-verified estimates based on comprehensive investigations of the method. It can also be concluded that comparisons between test results and acceptance limits have to be made with regard to the actual circumstances, as, e.g. how the acceptance limit is related to the risk. In the second case, the variation in the property of the material or product dominates and the uncertainty of the testing procedure is negligible. When the results are non-quantitative (go – no go), statistical methods can be used to estimate the risk taken with a certain sampling and acceptance strategy that a certain proportion of the batch to be delivered does not qualify. This should be considered more often in standardisation of product test methods. When the results are quantitative, a statistical analysis should be performed and the uncertainty should be compared with the acceptance limit as before, from the actual circumstances. When effects of testing uncertainty and product variation are comparable a sound treatment requires extensive experimental work. No short cuts can be made without loss of confidence! Received: 17 August 2001 Accepted: 21 March 2002     

Characterization of acceptance sets for co-monotone risk measures

We present a geometric characterization of acceptance sets for monotone, co-monotone and convex risk measures on finite state spaces. Geometrically, such acceptance sets can be represented by convex polygons with edges only on certain hyperplanes. We also provide some lower dimensional examples, and study acceptance sets for value at risk and expected shortfall.     

Determining nanomaterials in food

Nanotechnology has emerged as one of the most innovative technologies and has the potential to improve food quality and safety. However, there are a few studies demonstrating that nanomaterials (NMs) are not inherently benign.This review highlights some current applications of NMs in food, food additives and food-contact materials, and reviews analytical approaches suitable to address food-safety issues related to nanotechnology.We start with a preliminary discussion on the current regulatory situation with respect to nanotechnology in relation to foods. We cover sample preparation, imaging techniques (e.g., electron microscopy, scanning electron microscopy and X-ray microscopy), separation methods (e.g., field-flow fractionation and chromatographic techniques) and detection or characterization techniques (e.g., light scattering, Raman spectroscopy and mass spectrometry). We also show the first applications of the analysis of NMs in food matrices.     

An accredited laboratory's view of customer expectations

 Accredited laboratories are the accreditation bodies customers – all other interested parties are stakeholders. The ultimate consumer expects his product to be safe, reliable and good value for money. All other expectations in the supply chain relate to the consumer's expectations.     

Cost-optimal multistage sampling plans in statistical quality control

Multistage Bayesian decision procedures in statistical quality control are known from attribute sampling. In this paper they are introduced in a more general framework occuring in lot-control by using the theory of Bayesian sequentially planned decision procedures. We show that under sufficiency and transitivity assumptions and monotonicity properties concerning the distribution and cost set-up these Bayes-procedures have (z, c ^–,c ⁺)-structure which, on one hand, generalizes results of K.-H. Waldmann and, on the other hand, reduces computational effort significantly. Finally, examples taken from attribute sampling and life testing for an outgoing lot are presented.The theory presented in this paper is taken from [11].