California Sexually Violent Predator (SVP) Evaluations in the Field: Static-99R and Diagnostic Field Reliability

Tests and diagnoses used in sexually violent predator (SVP) evaluations must be reliable, as reliability is foundational to validity. The current study contained a stratified sample of evaluations of 395 individuals referred as potential SVPs between 2012 and 2017. Each individual was initially evaluated by at least two experts. The sample included three groups: individuals not meeting SVP criteria ( N = 200, or 400 evaluations), individuals meeting SVP criteria ( N = 95, with 190 evaluations), and individuals where evaluators disagreed ( N = 100, with 200 evaluations). The sample also included 200 subsequent independent evaluations on these “disagree” cases. Static-99R score intraclass coefficient (ICC) interrater reliability was good to excellent within each group and overall. Evaluators scored the Static-99R within one point of each other 87% of the time. Cohen’s kappa diagnostic agreement for Pedophilic Disorder was substantial. ASPD and substance abuse kappa were in the “fair” range, while OSPD diagnoses in the positive group were at the “moderate” level of agreement. Ethnic differences in diagnoses were consistent with other studies, with equivalent Static-99R ICC values across ethnic groups. There were no significant differences between state civil servants versus contracted experts in Static-99R ratings or final determinations. The results suggest that Static-99R scores have acceptable reliability in these evaluations, and Pedophilic Disorder (the most common paraphilic disorder in our study) and OSPD can be reliably diagnosed. We discuss limitations of the study, as well as the need for care in high-stakes evaluations given the imperfect reliability of psychological measurements.

Reliability-Informed Economic and Energy Evaluation for Design for Remanufacturing: A Case Study on a Hydraulic Manifold

Design for Remanufacturing (DfRem) is an attractive approach for sustainable product development. Evaluation of DfRem strategies, from both economic and environmental perspectives, at an early design stage can allow the designers to make informed decisions when choosing the best design option. Studying the long-term implications of a particular design scenario requires quantifying the benefits of remanufacturing for multiple life cycles while considering the reliability of the product. In addition to comparing designs on a one-to-one basis, we find that including reliability provides a different insight into comparing design strategies. We present a reliability-informed cost and energy analysis framework that accounts for product reliability for multiple remanufacturing cycles within a certain warranty policy. The variation of reuse rate over successive remanufacturing cycles is formulated using a branched power-law model which provides probabilistic scenarios of reusing or replacing with new units. To demonstrate the utility of this framework, we use the case study of a hydraulic manifold, which is a component of a transmission used in some agricultural equipment, and use real-world field reliability data to quantify the transmission’s reliability. Three design improvement changes are proposed for the manifold and we quantify the costs and energy consumption associated with each of the design changes for multiple remanufacturing cycles.

Field Reliability Estimation of Agricultural Tractors Based on Warranty Data

HighlightsA LightGBM regression model for predicting tractor usage rates was established based on warranty data and considering agricultural tractors’ usage context (region and season) and was then interpreted using SHAP.The field reliability of tractors was estimated based on the usage of failed and unfailed tractors, after unfailed tractors’ usage was imputed using the LightGBM regression model.The proposed methodology was validated by predicting warranty claims using estimated reliability parameters.The proposed methodology was demonstrated using warranty data from a tractor manufacturing company in China.Abstract. Warranty data provide a valuable source of information for assessing the reliability of products in operation (called the field reliability). However, warranty data consist of failure information only. The unavailability of usage data for unfailed products makes it difficult to estimate the reliability of durable products such as agricultural tractors, for which usage is a greater concern than age for reliability analysis. Several studies have proposed methods to address this problem, but they did not include information on the usage context. This study proposes a methodology to estimate the field reliability of agricultural tractors from warranty data considering the tractors’ usage context. First, by taking features representing tractors’ usage context as the input, a usage rate regression model was established using a light gradient boosting machine (LightGBM). The usage of unfailed tractors was then generated. Finally, parametric estimates of the tractors’ reliability were determined based on the usage of failed and unfailed tractors. By interpreting the LightGBM model using SHapley Additive exPlanations (SHAP), it was found that tractors that were used more days in October and April had higher predicted usage rates. To validate the effectiveness of the proposed methodology, the estimated reliability parameters were used to predict the warranty claims of six types of tractors. The results showed that the proposed methodology performed the best in four cases and close to the best in two other cases when compared with two other baseline methods. The proposed methodology was demonstrated using warranty data from an agricultural tractor manufacturing company in China and can be applied to improve understanding of tractor reliability. Keywords: Field reliability, LightGBM, SHAP, Usage context, Warranty data.

Reliability-Informed Life-Cycle Warranty Cost Analysis: A Case Study on a Transmission in Agricultural Equipment

In agricultural and industrial equipment, both new and remanufactured systems are often available for warranty coverage. In such cases, it may be challenging for equipment manufacturers to properly trade-off between the system reliability and the cost associated with a replacement option (e.g., replace with a new or remanufactured system). To address this problem, we present a reliability-informed life-cycle warranty cost (LCWC) analysis framework that enables equipment manufacturers to evaluate different warranty policies. These warranty policies differ in whether a new or remanufactured system is used for replacement in the case of product failure. The novelty of this LCWC analysis framework lies in its ability to incorporate real-world field reliability data into warranty policy assessment using probabilistic warranty cost models that consider multiple life cycles. First, the reliability functions for the new and remanufactured systems are built as the time-to-failure distributions that provide the best-fit to the field reliability data. Then, these reliability functions and their corresponding warranty policies are used to build the LCWC models according to the specific warranty terms. Finally, Monte Carlo simulation is used to propagate the time-to-failure uncertainty of each system, modeled by its reliability function, through each LCWC model to produce a probability distribution of the LCWC. The effectiveness of the proposed reliability-informed LCWC analysis framework is demonstrated with a real-world case study on a transmission used in some agricultural equipment.