Product Engineering

2005 ◽  
pp. 40-47
Author(s):  
Thomas Fischer ◽  
Janet Abrams
Keyword(s):  
Product Engineering

ATE Failure Isolation Methodologies for Failure Analysis, Design Debug and Yield Enhancement

1998 ◽  
Author(s):  
D.S. Patrick ◽  
L.C. Wagner ◽  
P.T. Nguyen
Keyword(s):  
Integrated Circuits ◽  
Failure Analysis ◽  
Yield Enhancement ◽  
Production Test ◽  
Final Test ◽  
Critical Design ◽  
The Past ◽  
Product Engineering ◽  
Time Savings ◽  
Analysis Design

Abstract Failure isolation and debug of CMOS integrated circuits over the past several years has become increasingly difficult to perform on standard failure analysis functional testers. Due to the increase in pin counts, clock speeds, increased complexity and the large number of power supply pins on current ICS, smaller and less equipped testers are often unable to test these newer devices. To reduce the time of analysis and improve the failure isolation capabilities for failing ICS, failure isolation is now performed using the same production testers used in product development, multiprobe and final test. With these production testers, the test hardware, program and pattern sets are already available and ready for use. By using a special interface that docks the production test head to failure isolation equipment such as the emission microscope, liquid crystal station and E-Beam prober, the analyst can quickly and easily isolate the faillure on an IC. This also enables engineers in design, product engineering and the waferfab yield enhancement groups to utilize this equipment to quickly solve critical design and yield issues. Significant cycle time savings have been achieved with the migration to this method of electrical stimulation for failure isolation.

Informationsqualität in der Produktentwicklung: Modellbasiertes Systems Engineering mit expliziter Berücksichtigung von Unsicherheit/Information Quality in Product Engineering: Model-Based Systems Engineering in Explicit Consideration of Uncertainty

Konstruktion ◽  
2020 ◽  
Vol 72 (11-12) ◽  
pp. 76-83
Author(s):  
Jens Pottebaum ◽  
Iris Gräßler
Keyword(s):  
Systems Engineering ◽  
Information Quality ◽  
Engineering Model ◽  
Model Based ◽  
Product Engineering ◽  
Explicit Consideration ◽  
Model Based Systems Engineering

Inhalt Unscharfe Anforderungen, verschiedene Lösungs-alternativen oder eingeschränkt gültige Simulationsmodelle sind Beispiele für inhärente Unsicherheit in der Produktentwicklung. Im vorliegenden Beitrag wird ein modellbasierter Ansatz vorgestellt, der das industriell etablierte Denken in Sicherheitsfaktoren um qualitative Aspekte ergänzt. Modelle der Informationsqualität helfen, die Unsicherheit von Ent- wicklungsartefakten beschreibend zu charakterisieren. Mittels semantischer Technologien wird Unsicherheit so wirklich handhabbar – nicht im Sinne einer Berechnung, sondern im Sinne einer qualitativen Interpretation. Dadurch entsteht wertvolles Wissen für die iterative Anforderungsanalyse, die Bewertung alternativer System-Architekturen oder für die Rekonfiguration von Simulationen.

scholarly journals Finite Queueing Modeling and Optimization: A Selected Review

2014 ◽  
Vol 2014 ◽  
pp. 1-11 ◽  
Author(s):  
F. R. B. Cruz ◽  
T. van Woensel
Keyword(s):  
Performance Evaluation ◽  
Queueing Networks ◽  
Queueing Network ◽  
Expansion Method ◽  
Network Analyzer ◽  
Modeling And Optimization ◽  
Product Engineering ◽  
Service Rates

This review provides an overview of the queueing modeling issues and the related performance evaluation and optimization approaches framed in a joined manufacturing and product engineering. Such networks are represented as queueing networks. The performance of the queueing networks is evaluated using an advanced queueing network analyzer: the generalized expansion method. Secondly, different model approaches are described and optimized with regard to the key parameters in the network (e.g., buffer and server sizes, service rates, and so on).

Method for localisation of sound sources and aggregation to an acoustic centre

2021 ◽  
Vol 263 (6) ◽  
pp. 894-906
Author(s):  
Yannik Weber ◽  
Matthias Behrendt ◽  
Tobias Gohlke ◽  
Albert Albers
Keyword(s):  
Sound Source ◽  
Single Point ◽  
Construction Cost ◽  
Measurement Technology ◽  
Front Part ◽  
Sound Sources ◽  
Preliminary Work ◽  
Product Engineering ◽  
Driving Conditions

Preliminary work by the IPEK - Institute of Product Engineering at KIT has shown that the simulated pass-by measurement for exterior noise homologation of vehicles has relevant optimization potential: the measurement can be carried out in smaller halls and with a smaller measurement setup than required by the norm and thus with less construction cost and effort. A prerequisite for this however is the scaling of the entire setup. For the scaling in turn, the sound sources of the vehicle must be combined to a single point sound source - the acoustic centre. Previous approaches for conventional drives assume a static centre in the front part of the vehicle. For complex drive topologies, e.g. hybrid drives, and unsteady driving conditions, however, this assumption is not valid anymore. Therefore, with the help of an acoustic camera, a method for localizing the dominant sound sources of the vehicle and a software-based application for summarizing them to an acoustic centre were developed. The method is able to take into account stationary, unsteady and sudden events in the calculation of the acoustic centre, which is moved as a result. Using substitute sound sources and two vehicles, the method and the used measurement technology were examined and verified for their applicability.

Das intelligente Instandhaltungssystem/The intelligent maintenance system - An approach for the self-learning structuring of maintenance libraries

2017 ◽  
Vol 107 (07-08) ◽  
pp. 530-535
Author(s):  
T. Miebach ◽  
M. Schmidt ◽  
P. Prof. Nyhuis
Keyword(s):  
Collaborative Research ◽  
The Self ◽  
Research Centre ◽  
Maintenance System ◽  
Intelligent Maintenance ◽  
Product Engineering ◽  
The Right ◽  
Self Learning ◽  
Intelligent Maintenance System

Der Fachbeitrag stellt eine Methode vor, mit der sich Bibliotheken von Instandhaltungsmaßnahmen selbstlernend gestalten lassen. Die „Intelligenz“ solcher Systeme bietet mehrfachen Nutzen, einerseits durch die Auswahl der passenden Instandhaltungsmethode zum richtigen Zeitpunkt, andererseits durch die damit verbundene Erhöhung des kompletten Abnutzungsvorrates. Die Ergebnisse sind im Sonderforschungsbereich 653 „Gentelligente Bauteile im Lebenszyklus – Nutzung vererbbarer, bauteilinhärenter Informationen in der Produktionstechnik“ entstanden.   This article describes a method to design a self-learning maintenance library. The benefit derived from the intelligence of those systems refers to the right choice of maintenance measures at the right time and the enhancement of the whole wear margin. The results are part of the Collaborative Research Centre 653: Gentelligent components in their lifecycle – Utilization of inheritable component information in product engineering.

scholarly journals Agile product engineering through continuous validation in PGE – Product Generation Engineering

2017 ◽  
Vol 3 ◽  
Author(s):  
Albert Albers ◽  
Matthias Behrendt ◽  
Simon Klingler ◽  
Nicolas Reiß ◽  
Nikola Bursac
Keyword(s):  
New Product ◽  
Engineering Process ◽  
Shape Variation ◽  
Engineering Model ◽  
Mechatronic Systems ◽  
Ongoing Activity ◽  
Product Engineering ◽  
Product Generation ◽  
Central Activity ◽  
Development Methods

Most products are developed in generations. This needs to be considered with regard to development methods and processes to make existing knowledge available to achieve increased efficiency. To realize this, the approach of PGE – product generation engineering – is formulated. Product generation engineering is understood as the development of products based on reference products (precursor or competitor products). The subsystems are either adapted to the new product generation by means of carryover or they are newly developed based on shape variation or principle variation. Validation is considered as the central activity in the product engineering process and is a major challenge, especially for complex mechatronic systems. Therefore, it is important to understand validation as an ongoing activity during product development. The pull principle of validation describes the definition and development of validation activities, including models and validation environments based on specific validation objectives. In order to have effectiveness within validation of subsystems, it is necessary to map the interactions with the overall system, namely the super-system. The relevant subsystems can be connected under consideration of functional and energetic aspects by means of virtual, physical or mixed virtual–physical modeling applied by the holistic IPEK-X-in-the-Loop approach within the integrated Product engineering Model (iPeM).

scholarly journals Computational intelligence in product design engineering: review and trends

2021 ◽  
Author(s):  
Filippo A. Salustri
Keyword(s):  
Decision Making ◽  
Product Design ◽  
Engineering Design ◽  
Computational Intelligence ◽  
Design Automation ◽  
State Of The Art ◽  
Design Engineering ◽  
Broad Perspective ◽  
Research Issues ◽  
Product Engineering

Product design engineering is undergoing a transformation from informal and largely experience-based discipline to a science-based domain. Computational intelligence offers models and algorithms that can contribute greatly to design formalization and automation. This paper surveys computational intelligence concepts and approaches applicable to product design engineering. Taxonomy of the surveyed literature is presented according to the generally recognized areas in both product design engineering and computational intelligence. Some research issues that arise from the broad perspective presented in the paper have been signaled but not fully pursued. No survey of such a broad field can be complete, however, the material presented in the paper is a summary of state-of-the-art computational intelligence concepts and approaches in product design engineering. Keywords: Computational intelligence, engineering design, product engineering, decision making, design automation

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