Peter Hammersberg

Facilitating decision-making by choosing an NDT method based on information need

This paper discusses the choice of an NDT method (non-destructive testing) from an information need perspective. It bridges the gap between technical methods, monitoring procedures and the need for information in an industrial application. The simple pull approach described starts from the decision that needs to be taken rather than from a previous data push procedure. That makes it more likely to match the method with the actual need, which leads to more effective and efficient evaluations. The pull approach is described by using a case from the welding industry, evaluation of the weld toe radius. The toe radius, defining how smooth the transition between the plate and the weld is, has been found critical to fatigue strength. Depending on the internal customer’s need of information, various evaluation solutions are preferred. The methods range from manual gauges to fully automated camera solutions. An interview study performed shows that the current process for choosing evaluation method differs. The person needing the information is often not the starting point in the process. A change in starting point influences both the choice of NDT method and visualization and thereby how efficient and effective the decision-making support will be. The financial effect is significant.

Emulation of POD curves from synthetic data of phased array ultrasound testing

Reliability of non-destructive techniques (NDT) is traditionally quantified by experimental determined probability of detection (POD). Such multi-parameter variability studies require a significant amount of experiments for each application verified, making them extremely costly. Reducing the need of experimental data by simulations requires both a verified simulation model and a procedure for effective computer experiments. Here synthetic POD curves for ultrasonic phased array testing have been generated using simSUNDT for signal amplitude simulations and a procedure to emulate response variability by predictive (meta) modeling and Monte Carlo simulations.

Pod generated by Monte Carlo simulation using a meta-model based on the simSUNDT software

A recent developed numerical procedure for simulation of POD is used to identify the most influential parameters and test the effect of their interaction and variability with different statistical distributions. With a multi-parameter prediction model, based on the NDT simulation software simSUNDT, a qualified ultrasonic procedure of personnel within Swedish nuclear power plants is investigated. The stochastical computations are compared to experimentally based POD and conclusions are drawn for both fatigue and stress corrosion cracks.

Variation of Tensile Properties of High Silicon Ductile Iron

The casting processes are characterized by complex relationships between predictors and responses. It is the fundamental understanding of these complex relationships that often involves hundreds of factors, which improves quality without losing productivity and raising cost. In this work, cast solid solution strengthened ferritic spheroidal graphite irons GJS-500-14 and GJS-600-10 (EN 1563:2012) have been evaluated. These materials offer stronger components with good machinability owing to their even hardness properties. In this case the predictors are chemical composition, gating layout, foundry set-up, testing procedure and equipment etc. and the responses are the tensile properties (Rp0.2, Rm, A5). Here 200 tensile specimens compiled from industrial foundry melts from over 30 years of research have created a state-of-the-art platform for statistical engineering in order to perform Exploratory Data Analysis (EDA) and data visualization. This statistical platform has provided new insight on how foundries should treat complex relationships between predictors and responses in order to identify sources of variation and interaction effects.

Factors influencing control charts usage of operational measures

Purpose The purpose of this paper is to identify factors influencing implementation of control charts on key performance indicators (KPIs). Design/methodology/approach Factors driving organizational change described in literature are analyzed inspired by the affinity-interrelationship method. A holistic multiple-case design is used to conduct six workshops to affect the usage of control charts on KPIs at a global company in the automotive industry. The theoretical factors are compared with the result from the case study. Findings The important factors for implementation success differ to some extent between the theoretical and empirical studies. High-level commitment and a clear definition of the goal of change could be most important when creating a motivation for change. Thereafter, having a dedicated change agent, choosing an important KPI and being able to describe the gain in financial terms becomes more important. Practical implications By using control charts on KPIs, the organization in the case study has become more proactive, addressing the right issues upstream in the process, in the right way, cross-functionally. Originality/value Factors affecting the implementation of already available solutions in the industry are highlighted. This potentially provides a basis for improved decision making, which has a significant value.

The Potential in Simulation and Metamodeling for the Understanding and Development of NDE

Abstract By combining detailed mathematical modeling of the physics involved in NDE with a broader and robust engineering approach based on the sequential steps of screening, modeling and optimization, it is possible to generate metamodels that can support NDE engineering efforts to evaluate the applicability of NDE in a wider context, as a complement to the repeatability, reproducibility and capability studies normally performed. The aim of the initial screening phase is to effectively evaluate and prioritize NDE control parameters from a wider perspective regarding the demands of a specific application and to prioritize parameters of lesser importance for the outcome on the basis of economic and practical considerations. The aim of the second and third steps is to study the influence of the important parameters and to perform sensitivity analyses of reproducibility and repeatability, for example, followed by procedure development, respectively. The methodology is straightforward when it comes to smooth response surfaces of lower order (up to second or third order). Generally, the recommendation for the screening phase is ‘to be bold’ for the definition of the experimental range for each parameter – meaning to make them as wide as possibly relevant for the specific application. For NDE applications not following the Berens assumption for POD studies, e.g., large cracks yield large response signals, such as the varying signal amplitudes from surface breaking notches in ultrasonic testing, the mentioned recommendation of ‘be-bold’ screening phase may lead to incorrect prioritization of parameters. In this publication, this is illustrated by how the width of the experimental range for the control parameters tested during screening actually influences the screening results. Two basic ultrasonic testing set-ups have been compared using the SimSUNDT simulation software package: surface breaking notch (SBN) and side drilled hole (SDH). Even though the results were anticipated, they pointed out the need to further develop the screening methodology supporting NDE engineering, especially when it comes to addressing the issue of applicability. Does the data collected tell us what we actually want to know about the tested application? Or does it only tell us something about the NDE method?