Self-Resilient Systems: Closed-Loop Life-Cycle Engineering Digital-Product Lifecycle Management (D-PLM)

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Digital-Product Lifecycle Management (D-PLM)
Self-Resilient Systems: Closed-Loop Life-Cycle Engineering
The D-PLM group develops methodologies that integrate product design, manufacturing and service to create a
novel close-loop life-cycle modeling and synthesis framework, self-resilient production system, which
can self-recover from engineering changes and 6-sigma faults.
In doing so, it breaks new ground by
establishing a research field on the interface between tangible product design, manufacturing and intangible
services. This will impact a range of high value products, with potentially profound effects on PLM
methodologies in a number of industries including automotive, aerospace, consumer goods and healthcare.
Introduction
Proposed Research Framework
Frequent and unpredictable market changes combined with ever
greater customer expectations have increased the complexity of
modern industrial systems; rapidly shortening time available for their
development. This has led to a crucial need to reduce or eliminate
especially 6-sigma(6-s)/variation faults during product lifecycle. This
means that achieving dependability of current and future
interconnected industrial systems will require tremendous advances in
the development of fundamental methods and simulation approaches
that can effectively and efficiently integrate design, manufacturing and
service engineering models with heterogeneous measurement data
captured during manufacturing and service phases (see figure below).
Develop the concept of self-resilient systems by integrating:
Research challenges in PLM area addressed by the DPLM Group
No surprise should be expected in these phases
Design Synthesis
• Stream-of-variation
• Design Tasks
• Eng. Changes
Validated
Models
Validate product and
processes with uncertainty
and incomplete early design
information
Make &
Test
Ramp-up
Operate &
Service
Ramp-up Synthesis
• 6-s fault diagnosis
• Process adjustment
• Sensor networks
Service synthesis
Reduce time needed
to diagnose/recover
from 6s faults?
Shorten lead time
(2) Production ramp-up synthesis focuses on 6-sigma fault: (i) root
cause analysis; and, (ii) self-recover from faults through process
adjustment.
(3) Service synthesis focuses on No-Fault-Found (NFF): (i) root cause
analysis; and, (ii) self-recover from faults through adjustments.
Self-resilience framework
State of the Art
CHALLENGES
REQUIREMENTS
Digital
Models of
Product
and
Process
Family
(1) Design synthesis focuses on math-based design-manufacturing
integration via developing methods for individual design tasks and
framework for their integration;
Reduce number of
service failures
• No-Fault-Found
• Remote diagnosis
• System Modelling
& Improvement
Product Lifecycle Management
No Adjustability
No Adjustments
No Adjustments
No Diagnosability
No Diagnosis
No Diagnosis
Robustness
Monitoring
Monitoring
DESIGN
CAD / CAM / CAPP
MANUFACTURING / PRODUCTION
Station 1
...
Station k
... Station N
PRODUCT
FIELD / SERVICE
End-of-line
sensing
Event log
Warranty
data
Monitoring
Robustness
Monitoring
Diagnosability
Diagnosis
Diagnosis
Adjustability
Adjustments
Adjustments
Self--Resilience Framework
Self
Challenges
Trial and error
Developing such methods demands an interdisciplinary focus that can
effectively integrate design models (CAD), system engineering models
(product/process
architecture;
performance
optimization),
manufacturing models (CAM), control engineering models, statistical
models (data with large sample size and small dimensionality), and
computer engineering and data mining models (data with relatively
small sample size and large dimensionality).
Current and the proposed criteria for closed-loop lifecycle synthesis
Intra--loop
Intra
Inter--loop
Inter
The DPLM Research Roadmap
Engineering Assessment: Loss Function
KCs
KCs
KCs
NFF
region
LSL
Design
nominal
USL
Design
nominal
LSL
Deterministic
USL
LSL Functional Design
nominal nominal
Lean
USL
Self-Resilience
Mean adjustment Variation reduction
Robustness
+
Tolerance
range
Worst case
scenario
State of the Art
Tolerance
range
Tolerance
range
6s -Diagnosability
6s-Diagnosability
+
Service fault
region
6s
6
s -Adjustability
No-Fault-Found
Design Gen 1
Design Gen 2
Robustness
Proposed
For more information contact: Prof. Eduardo Izquierdo, Prof. Darek Ceglarek {L.E.Izquierdo, d.j.ceglarek }@warwick.ac.uk or http://digiPLM.org/
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