ENBIS-18 in Nancy2 – 25 September 2018; Ecoles des Mines, Nancy (France) Abstract submission: 20 December 2017 – 4 June 2018
The following abstracts have been accepted for this event:
Effect of the Prior Distribution on the Mean in Control Charts
Authors: Isabel Ramírez (Universidad Nacional de Colombia), Nelfi González (Universidad Nacional de Colombia)
Primary area of focus / application: Quality
Secondary area of focus / application: Quality
Keywords: Control charts, ARL, Bayesian approach, Normal distribution
Submitted at 25-Apr-2018 15:05 by Isabel Ramírez
Accepted (view paper)
Prediction Uncertainty of Times Series and State Space Models
Authors: Bjarne Bergquist (Luleå University of Technology), Peter Söderholm (Swedish Transport Administration and Luleå University of Technology)
Primary area of focus / application: Reliability
Keywords: Railway, Track geometry, Remaining useful life (RUL), Uncertainty, Kalman Filter, Time series, Prediction
Submitted at 26-Apr-2018 09:35 by Bjarne Bergquist
Track property sampling is irregular, and measurement errors differ between measurements. We compare models where we have assumed the same measurement error with models where we use the estimated precision of each measurement. The irregular sampling makes lumping of measurements into time intervals needed. We, therefore, analyse different interval selections for lumping of data. We also address needs for non-linear models and possibilities for seasonal component estimations.
Run-to-Run Control Based on Gaussian Bayesian Network in Semiconductor Manufacturing
Authors: Wei-Ting Yang (École des Mines de Saint-Étienne), Jakey Blue (École des Mines de Saint-Étienne), Agnès Roussy (École des Mines de Saint-Étienne), Marco S. Reis (University of Coimbra), Jacques Pinaton (STMicroelectronics)
Primary area of focus / application: Process
Secondary area of focus / application: Mining
Keywords: Run-to-Run (R2R), Fault Detection and Classification (FDC), Virtual Metrology (VM), Equipment signal, Gaussian Bayesian Network (GBN)
Submitted at 26-Apr-2018 09:50 by Wei-Ting Yang
For this aim, Gaussian Bayesian Network (GBN) is employed to analyze the implicit relationship not only between the control factors and process parameters but also among the process parameters and metrology. The cause-effect relationship between all the variables can be explicitly expressed in the form of a connected graph after applying GBN. Consequently, the variation of process parameters caused by the control factors can be estimated and the corresponding predicted metrology can be obtained simultaneously. In this regard, we are able to consider process control in a more global view.
The effectiveness of this approach is demonstrated and validated via a practical case study, in collaboration with our industrial partner.
Insight into Aftermarket Automotive Sales, Factory Standards and Predicting Autopart Replacement
Authors: Wayne Smith (Rain Data / Newcastle University), Shirley Coleman (Newcastle University), Jaume Bacardit (Newcastle University)
Primary area of focus / application: Quality
Keywords: Automotive aftermarket, Shewhart chart, Control limits, Return rates, Fuzzy matching, OEM standards
Submitted at 26-Apr-2018 13:47 by Shirley Coleman
Accepted (view paper)
Returns are an important consideration in any business that supplies goods. Returns can cost a company for many reasons, including, the cost of posting and identifying if a product is fit for re-sale. Here, the return rates of frequently bought car parts are plotted as a Shewhart chart, using a funnel plot with statistical limits to identify which return rates require investigation. This allows a method to prioritise attention to parts according to whether (and by how much) the return rates lie beyond the 3 standard deviation limits of the control chart.
When referring to car parts, the OEM standard refers to the manufacturer of the original equipment - that is, the parts assembled and installed during the construction of a new vehicle. The aftermarket parts are those made by companies trying to match the OEM factory standard. There is considerable uncertainty about which parts match to which OEM numbers. The analysis presented here uses fuzzy matching to compare supplier parts to typical OEM factory standards. This process reveals those supplier parts which can be matched against other cars to which they weren’t originally intended, and in doing so highlights potential revenue for a supplier, in which they can sell their part against cars without modifying their product.
Comparing invoices for replacement car parts and noting the mileage of the car at the time of replacement highlights the potential failure rate of non-serviceable car parts. Inspecting those parts that were replaced (along with the mileage at the point of replacement) and comparing these across different car models also demonstrates the reliability different car manufacturers. Function fitting of the part replacement per mileage aids in the process of identifying key points in a car’s history when failure may occur. This presentation explains this method in further detail.
Investigating the Influence of Different Powders on Coating Properties in an HVOF Spraying Process
Authors: Eva-Christina Becker-Emden (Dortmund University of Applied Sciences and Arts)
Primary area of focus / application: Modelling
Secondary area of focus / application: Design and analysis of experiments
Keywords: Thermal spraying, Protective coatings, Generalized linear models, Model selection, Factorial design, Blocking
Submitted at 26-Apr-2018 14:03 by Eva-Christina Becker-Emden
To investigate differences between powders we run a factorial design with additional center points on two subsequent days, which is blocked and repeated for every powder. Taken into account are a WC-12Co powder of the type WOKA 3102 from Sulzer Metco, a WC-Co powder with small carbides, a WC-FeCrAl powder and a Cr3-C2 powder. We compare the obtained coating and particle properties for the different powders graphically. Additionally, we fit generalized linear models for some properties to gain insight into the influence of the process settings. Our model building is based on an all-subset selection using the Bayes Information Criterion as a selection criterion with the maximal model including all main effects. We consider different link functions under the assumption of gamma-distributed responses.
We find that the WC-based powders provide a similar behaviour. In future, further experiments with the Cr3-C2 powder could be of interest, as its behaviour deviates from the WC-based powders.
Preserving Projections Properties when Regular Two-Level Designs are Blocked
Authors: John Tyssedal (The Norwegian University of Science and Technology), Yngvild Hamre (The Norwegian University of Science and Technology)
Primary area of focus / application: Design and analysis of experiments
Keywords: Regular two-level designs, Blocking, Projective properties, Confounding
Submitted at 27-Apr-2018 10:32 by John Tyssedal