Stefan Bracke

CDMF-RELSUS concept: reliable products are sustainable products – influences on product design, manufacturing and use phase

Based on the customer’s product recognition, sustainability and environmental protection become key sales arguments within the automotive industry. The customer expects reduced resource consumptions, environmental friendly manufacturing and a long usage phase. Especially product reliability saves resources in many ways. Manufacturer product reliability is associated with higher development and production costs, but, especially in industries with high innovation rates, customer usage is limited to the product actuality, which leads to two key questions: a) How much product reliability makes sense out of the view of manufacturers, customers and environmental protection? b) What is the impact of reliable products regarding the reduction of resources? This paper outlines the ‘Collaborative development, manufacturing and field verification for higher product reliability towards sustainability (CDMF-RELSUS) concept’ focusing on influences and interdependences of product development, manufacturing planning and f...

Upgradable Design for Reduction of Production Cost and CO2 Emission - Case Study of a Laptop Computer

An upgrade product design method is one of the efficient design methods for reducing environmental loads caused by mass production, consumption, and disposal. This method seeks to design a product that can adapt to future required performance and functions via component upgrade by exchanging components in the early phase of design. Because considerations of future product performance and functions include uncertain design information, an accurate prediction is very difficult. Therefore, this study defines uncertain design information as ranged sets, and applies a preference set-based design method that can correspondingly obtain ranged sets of design solutions. In previous studies, proposed methods were focused on product performance enhancement without quantitative consideration of environmental loads. Hence, this study proposes an upgrade product design method that can address the enhancement of product performance, while concurrently reducing production cost and environmental load, which is herein strictly defined as the amount of CO2 emission. Finally, our proposed upgrade product design method is applied to a laptop PC design problem to demonstrate its utility.

Optimization of test procedures based on OBD system specific field data

This paper shows the results of the research work with regard to optimization of test procedures based on systematic analysis of field behavior. The presented approach outlines all important steps of the overall process, the statistical methods and algorithms used with the help of an example from the automotive industry. The example is based on the data gathered during various rides with four different vehicles (BMW, Chevrolet, Opel and Peugeot) and stored with a data logger connected to an OBD II port. An important part of the approach is the mathematical and statistical analysis of stored signals, which are divided into two groups with regard to the characteristics of their dynamics. Furthermore, the importance and additional benefit of bi- and multivariate analysis of signals is summarized. The results of the signal analysis with all important information are prepared for further analysis of the distinctive functions of car fleets with the rule learning algorithms. The analysis is performed with three different algorithms (NNge, JRip and J48) which provide slightly different results. The performance of all three algorithms to the applied problem is discussed in detail. Nevertheless, the main result shows that the predefined rule (with 5, 10 and 15 attributes) can be found easily with the NNge algorithm. This means that the specific set of operating conditions (OCs) at which the claimed car operates can be distinguished from the rest of the fleet. The assumption for the set of OCs is that the specific, searched information is forwarded to the OBD II interface and stored by the data logger. The obtained set of OCs forms the basis for the optimization of the test procedures and update of the operating conditions of a certain product. The major steps of the optimization of the testing with regard to the present work are as follows: 1. Collect the adequate OBD data 2. Perform the analysis of all OBD signals in order to obtain the operating conditions of the product 3. Compare the gathered information of claimed and not-claimed vehicles to detect the distinctive features 4. Optimize the test conditions with regard to the obtained operating (test) conditions.

Reliability analysis regarding product fleets in use phase: Multivariate cluster analytics and risk prognosis based on operating data

The increasing complexity of product functionality and manufacturing process parameters often leads to complex failure modes and reliability problems within the product life cycle. Especially in the case of mass production of consumer goods - e.g. automobiles, washing machines, computer - an increasing percentage of damaged products within the product fleet can lead to garage or recall actions. If the manufacturer receives knowledge about the first damage claims based on a field observation, a risk probability prognosis is the base of operations regarding further actions. State of the art concerning risk calculation methods consider the failure behaviour and allow the univariate determination of the risk probability regarding the product fleet. These methods do not consider the load or usage profile of the products based on any life span variable. In fact, current technical complex products save a lot of life data (“Big Data”), which can be additionally used for risk analysis within product fleets. This paper outlines an approach to determine the risk probability in product fleets based on a combined multivariate analysis of the product failure behaviour and the customer product usage profile. The theory and application of the approach is shown with the help of a synthetic data set within an automotive case study, which includes real effects of typical field failure behaviour and usage profiles of an automobile fleet.

Reliability analysis of organic fibres using limited data

This paper shows the results of research work regarding analysis procedures for prototype test results, based on heterogeneous prototype characteristics and limited data within the early phase of product development. The research activities were applied within a case study “Organic fibre prototype analysis” from the chemical process industry. An example of an organic fibre is cotton. The research goal was the analysis of reliability parameters of heterogeneous fibre samples as a function of treatment. The treatment types were (a) untreated, (b) thermal treatment and (c) chemical treatment. The reliability parameter used herein is the number of cycles to failure (separation) of the fibre element under load in a linearly reciprocating test facility. The facility parameters are load (grams), stroke (mm) and frequency (Hz). The procedure used was to (a) determine the optimum facility settings, (b) perform the test on a sample set to determine cycles to failure, and (c) perform a statistical analysis of results. The main results are: 1. Facility adjustment concerning maximal differentiability is stroke 4 mm, frequency 1 Hz and weight 10 g. 2. Suggested facility adjustment concerning maximal differentiability is stroke 4 mm, frequency 2 Hz and weight 10g. 3. Thermal treatment has a significant decreasing influence on reliability characteristics of organic fibres. 4. Chemical treatment has a low decreasing influence on reliability characteristics of organic fibres. 5. Chemical treatment can be used for improving durability of organic fibres in contrary to thermal treatment. The used approach shows that the combined application of both nonparametric and parametric statistical methods is successful. The transfer of the approach to similar technical problems is feasible. The future scope of the research work will be the analysis of various treatments using the suggested facility adjustments and the appropriate determination of their influence on reliability characteristics.

A Design Method for Product Upgradability with Different Customer Demands

A sustainable society requires changes in the traditional paradigm of mass production and consumption. Products such as personal computers and smartphones are discarded even though they are fully functional. This paper proposes a design method for product upgradability which satisfies various different customer demands to increase the product value and extend the value lifespan by exchanging components closely related to its deterioration in value. In addition, this paper also proposes a method that can specify future product performances, effective upgradable product components, and the side effects of upgrade on other product components. Finally, this paper discusses the applicability of our proposed design method by considering a vacuum cleaner and various different customer demands.

IDREMA-process: Identification of reference market for defect parts routing

In the automotive industry the number of reports concerning large-scale product recalls of vehicles is increasing (cf. [1]) and thereby alarming not only affected but also future customers. Therefor the quality management of major automobile groups is facing an increasing challenge. The goal of a quick fault detection and removal is endangered by an increasing product complexity, an expansion of the international distribution into markets with highly divergent requirement profiles and a restricted access of defect parts from various countries. In order not to fall short of the objectives in the future, a concept for the “Worldwide Routing of Defected Parts in the Automotive Industries” (WORPA) is being developed. The idea is to deduce the fitting control option for providing the optimum analytical batch. Due to transport costs, customs duty issues, and the lack of necessary infrastructure, a worldwide access to every market with defect parts is neither available nor economically justifiable. Therefore it is common practice to define a market as a so-called reference market. This market should be representative of occurring failure modes depending on several boundary conditions such as climate, load profiles, stretches of way or fuel quality. Traditionally, the reference market is contractually fixed to be the domestic producer market. In an economically dynamic environment like the automotive industry, sales markets are continually shifting to countries with differing requirement profiles (e. g. China; fuel quality) and potential new failure modes. Thus, it is necessary to undertake a scientific review of the previously axiomatic selection of the reference market. In this article the “Identification of Reference Market” (IDREMA) process - as a part of the WORPA concept - is introduced and distinguished from other existing systems. The IDREMA process is a means to determine a reference market in a structured procedure. For this purpose, rudimentary prerequisites as well as qualitative and quantitative impacts concerning occuring failure modes are considered. The statistical analysis is based on the sampling range of dependable methods of testing. A synthesized practical example (Case Study Assembly Module) illustrates the way of proceeding.

OMSP: Failure detection based on small field part and data volumes

Increasing functionality and complexity of technical products result in complex damage symptoms and failure modes within the customer use phase. Especially in automotive industry, complex damage symptoms are often the result of multiple failure modes. Therefore the importance of continuous field product observation and field data analysis is an important way for analyzing product reliability in the use phase. For the manufacturer, the goals are the accurate and economic identification of possible failure modes and the knowledge of the product failure behavior based on field complaints at an early stage after product market launch. In addition to statistical reliability analysis based on field data (e.g. Weibull distribution analysis, RAW Concept), the technical analysis of damaged field components is an essential point for the detection and verification of individual failure modes. Especially for this technical analysis, the manufacturer needs damaged field components, which represent the whole supposed failure spectrum in the field. The goals for the manufacturer include: (1) Early and detailed detection and identification of critical failure modes, with the objective of targeted response to critical failure modes (2) Conjunction of requirements for the determination of the regress rate and detection of the critical failures in a comprehensive approach (cf. chapter 2) (3) Optimization of economic aspects of the reliability analysis in terms of sampling procedure, sampling analysis and technical analysis costs (4) Integration into existing technical analysis processes to establish and support an industry-specific standard The temporal aspect results in reduced field monitoring periods and therefore results in small damaged field part and data volumes. This requirement restricts the use of parametrical statistical methods and requires the use of nonparametric statistical methods. The results of field data and technical analysis generate the basis for a targeted roll out of further actions, for example field failure rectification or product optimization. Moreover the initiation of concentrated development-approaches /-strategies for failure prevention with respect to the subsequent product generations (e.g.: COP strategy) is feasible. An industry-wide or cross-industry approach for economic and optimized sampling procedures of damaged components out of the field does not exist. The Chair of Safety Engineering / Risk Management at the University of Wuppertal - in cooperation with manufacturers of the automotive industry - developed the Optimized Multi-Stage Sampling Procedures (OMSP) concept. The OMSP concept is a proposal regarding to analyzing standard for the automotive industry. Key aspects of the OMSP concept are as follows: (1) Early identification and analysis of critical failure modes with reduced amount of analyzed damaged components but with similar detection rate and resolution accuracy (2) Reducing costs of the technical analysis reduce the scope of analyzed damaged components with comparable detection rate of critical failure modes (3) Deselection of selected data areas to reduce the amount of data and the request of considered damaged components allows the verification of the reliability of technical component changes while drawing constant sample sizes (4) Recognition of critical failure modes allows targeted actions for troubleshooting, for example in the field or in the current product generation (5) Integration of the OMSP concept in the FDA process allows the verification of the potential failure modes detected by the statistical reliability analysis This paper outlines the effectiveness and use of the OMSP concept in a near reality case study of the automotive industry. The focus of the case study is the analysis of a shift by wire actuator module (consisting of an electric motor and electrical control unit) including different failure modes. The application of the OMSP concept shows the following essential results: On the one hand, a 50% reduction of requested damaged field components regarding to the technical analysis. On the other hand, the detection rate of critical failure modes based on the reduced analyzed field parts is almost the same in comparison to a full technical analysis of all damaged field components.

Field damage analysis (FDA) concept: Analysis of complex damage causes

Increasing functionality and complexity of technical products is resulting in complex damage symptoms and causes during customer usage phase. Especially in the automobile industry, complex damage symptoms are often traceable to multiple damage causes. This increases the importance of structured field product observation and field data analysis. For the OEM, the goals are high levels of quality and reliability that can be attained by comprehensive analysis of product performance, design and reliability over the whole product life cycle. This includes: • After product launch into the market: Early and accurate identification of possible and actual damage causes by analysis of failures provides knowledge of product failure behavior. This can be attained by analyzing the occurring failures based on small amount of field damage data. The cost implications should also be assessed. • Product life cycle: Detailed mapping and analysis of the long-term product failure behavior and reliability These generates the basis for a targeted introduction of further actions, for example rectification of faults in the field, product optimization, or the initiation of concentrated development approaches/-strategies for failure prevention (e.g.: COP strategies). Currently no industrial standard for reliability analysis can fulfill the requirements of a comprehensive reliability analysis over the entire product life cycle. Based on these requirements the FDA concept was developed by the Department of Risk Management and Safety Engineering at the University of Wuppertal, in cooperation with OEMs of the automotive industry. Key aspects of the FDA concept are as follows: • Integration of several statistical and organizational methods in a comprehensive process • Mapping product reliability over whole product life cycle • Statistical analysis of failure data — for example, relating to identification of possible damage causes, production batch differences or climatic influences • Usage of qualitative data and information of the value added network regarding potential damage causes that can reduce the costs of the technical analysis • Conjunction of the determination of the regress rate and detection of the critical failures (product quality analysis) in a comprehensive approach. Currently different requirements — made by the OEMs — avoid the conjunction, e.g. sampling procedures and sample size • Optimization of analysis costs in terms of sampling procedure, sampling analysis and technical analysis with respect to high detection rate of damage causes The paper outlines the process of the FDA concept. Moreover, the paper presents advanced methods (such as the DCD algorithm, WCF approach, OMSP concept and RAW concept; cf. chapter 2.2 and 2.3) and industrial methods (like Weibull distribution and Eckel candidate methods) to ensure the key aspects. Finally, the paper outlines the use of value added networks to gain more information about the damage causes before performing the technical reliability analysis. Therefore the FDA concept supports the mapping, identification and description of complex damage causes of complex components and systems in the automotive industry with the goal of early failure detection in the field and preventive reliability control of subsequent product generations.

Aperiodic Surface Topographies Based on High Precision Grinding Processes: Analysis of Cutting Fluid and Cleaning Process Influences Using Non-parametric Statistics

High precision manufacturing processes of technical product surfaces have to fulfil demanding requirements regarding functional characteristics like roughness, gloss and colour. Especially the reproducibility and control of aperiodic surface topographies based on grinding processes are influenced by many manufacturing process factors and cleaning methods. This paper outlines a concept for the multivariate analysis of measurement data regarding aperiodic surface topographies (characteristics: roughness and gloss) based on small sample sizes, varied process parameter and different cleaning methods. The concept and analysis are based on non-parametric statistics, due to the particular challenge which is the missing knowledge of the distribution models regarding to the characteristics roughness and gloss. The application of the worked out measurement strategy and the multivariate non-parametric statistical method is shown within a case study “Grinding surfaces of cutlery” comparing four different processes. The compared cleaning compounds are cold degreaser (standard method) and acetone (optional method) in combination with different technical grinding processes (cutting fluid fat respectively water based).