Uncertainty modelling for extended product lifecycles: Application of a biological analogy to product lifecycle management

Research output: Contribution to conferencePaper

Abstract

Product lifecycles are determined at a point in the planning process where there is great
uncertainty in future market conditions and drivers for change. Particularly for products with high
investment costs and long lifecycles, the period of production may be considerably longer than the
change cycle for new technical developments, legislation changes, market conditions, etc.
Using internal combustion (IC) engines as an exemplar of products with long planned lifecycles (10-
20 years) and heavy investments (~£200M), a model has been developed to help predict probable,
but uncertain, geometry changes in product architecture over expected lifecycles. The model draws
on a biological analogy to apply adaptive landscapes to product architecture choices, building in
robustness to requirements variation over the life of the product.
The model has been applied to historical examples of the evolution of a family of products from first
introduction, through to end of production. In this way, actual lifecycle extension, modification and
change can be compared to modelled approaches to validate heuristic values to be used in future
product planning.
The use of adaptive landscapes allows products to be defined in such a way that they are more
robust to ill-defined, but reasonably expected changes in product configurations and requirements.
Thus, reducing total lifecycle investment costs and allowing products to be more responsive to
changed circumstances. Through this process, the lifecycle of products can be extended for
minimized cost of change.
Original languageEnglish
Publication statusPublished - 17 Jun 2015
EventPLATE 2015: Product Lifetimes and the Environment - Nottinham Trent University, Nottingham, United Kingdom
Duration: 17 Jun 201519 Jun 2015

Conference

ConferencePLATE 2015
Abbreviated titlePLATE 2015
CountryUnited Kingdom
CityNottingham
Period17/06/1519/06/15

Fingerprint

Product lifecycle
Uncertainty modeling
Product lifecycle management
Life cycle
Costs
Market conditions
Product architecture
Heuristics
Legislation
Planning
Geometry
Combustion
Product configuration
Planning process

Bibliographical note

© 2015 The Author

Cite this

@conference{70343f537d4948cfbc59db3b4367c313,
title = "Uncertainty modelling for extended product lifecycles: Application of a biological analogy to product lifecycle management",
abstract = "Product lifecycles are determined at a point in the planning process where there is greatuncertainty in future market conditions and drivers for change. Particularly for products with highinvestment costs and long lifecycles, the period of production may be considerably longer than thechange cycle for new technical developments, legislation changes, market conditions, etc.Using internal combustion (IC) engines as an exemplar of products with long planned lifecycles (10-20 years) and heavy investments (~£200M), a model has been developed to help predict probable,but uncertain, geometry changes in product architecture over expected lifecycles. The model drawson a biological analogy to apply adaptive landscapes to product architecture choices, building inrobustness to requirements variation over the life of the product.The model has been applied to historical examples of the evolution of a family of products from firstintroduction, through to end of production. In this way, actual lifecycle extension, modification andchange can be compared to modelled approaches to validate heuristic values to be used in futureproduct planning.The use of adaptive landscapes allows products to be defined in such a way that they are morerobust to ill-defined, but reasonably expected changes in product configurations and requirements.Thus, reducing total lifecycle investment costs and allowing products to be more responsive tochanged circumstances. Through this process, the lifecycle of products can be extended forminimized cost of change.",
author = "Price, {Brian J}",
note = "{\circledC} 2015 The Author; PLATE 2015 : Product Lifetimes and the Environment, PLATE 2015 ; Conference date: 17-06-2015 Through 19-06-2015",
year = "2015",
month = "6",
day = "17",
language = "English",

}

Price, BJ 2015, 'Uncertainty modelling for extended product lifecycles: Application of a biological analogy to product lifecycle management' Paper presented at PLATE 2015, Nottingham, United Kingdom, 17/06/15 - 19/06/15, .

Uncertainty modelling for extended product lifecycles: Application of a biological analogy to product lifecycle management. / Price, Brian J.

2015. Paper presented at PLATE 2015, Nottingham, United Kingdom.

Research output: Contribution to conferencePaper

TY - CONF

T1 - Uncertainty modelling for extended product lifecycles: Application of a biological analogy to product lifecycle management

AU - Price, Brian J

N1 - © 2015 The Author

PY - 2015/6/17

Y1 - 2015/6/17

N2 - Product lifecycles are determined at a point in the planning process where there is greatuncertainty in future market conditions and drivers for change. Particularly for products with highinvestment costs and long lifecycles, the period of production may be considerably longer than thechange cycle for new technical developments, legislation changes, market conditions, etc.Using internal combustion (IC) engines as an exemplar of products with long planned lifecycles (10-20 years) and heavy investments (~£200M), a model has been developed to help predict probable,but uncertain, geometry changes in product architecture over expected lifecycles. The model drawson a biological analogy to apply adaptive landscapes to product architecture choices, building inrobustness to requirements variation over the life of the product.The model has been applied to historical examples of the evolution of a family of products from firstintroduction, through to end of production. In this way, actual lifecycle extension, modification andchange can be compared to modelled approaches to validate heuristic values to be used in futureproduct planning.The use of adaptive landscapes allows products to be defined in such a way that they are morerobust to ill-defined, but reasonably expected changes in product configurations and requirements.Thus, reducing total lifecycle investment costs and allowing products to be more responsive tochanged circumstances. Through this process, the lifecycle of products can be extended forminimized cost of change.

AB - Product lifecycles are determined at a point in the planning process where there is greatuncertainty in future market conditions and drivers for change. Particularly for products with highinvestment costs and long lifecycles, the period of production may be considerably longer than thechange cycle for new technical developments, legislation changes, market conditions, etc.Using internal combustion (IC) engines as an exemplar of products with long planned lifecycles (10-20 years) and heavy investments (~£200M), a model has been developed to help predict probable,but uncertain, geometry changes in product architecture over expected lifecycles. The model drawson a biological analogy to apply adaptive landscapes to product architecture choices, building inrobustness to requirements variation over the life of the product.The model has been applied to historical examples of the evolution of a family of products from firstintroduction, through to end of production. In this way, actual lifecycle extension, modification andchange can be compared to modelled approaches to validate heuristic values to be used in futureproduct planning.The use of adaptive landscapes allows products to be defined in such a way that they are morerobust to ill-defined, but reasonably expected changes in product configurations and requirements.Thus, reducing total lifecycle investment costs and allowing products to be more responsive tochanged circumstances. Through this process, the lifecycle of products can be extended forminimized cost of change.

M3 - Paper

ER -