4 research outputs found
Estimating cost at the conceptual design stage to optimize design in terms of performance and cost
In the highly competitive business environment, cost estimation is a
strategic tool, which can be used to assist decision making with regard to products
throughout their life cycle. 70 to 80 percent of the life-cycle costs of a product are
determined by decision taken by designers during the early design stages.
Therefore it is important to estimate and optimise cost as early and as accurately as
possible. The main aim of this research is to use typically available information at
the conceptual stage of design and estimate cost in order to optimise design in
terms of performance and cost. The main objective is to employ Design of
Experiments (Taguchi method) to use the sparse information more effectively in
order to estimate the cost of a product at the early design stage. This paper presents
the current status of the research activity. A case study is introduced which
illustrates the initial applications of the optimization process. Conclusions are then
discussed and the future research described
Uncertainty in through-life costing-review and perspectives
Estimating through-life cost (TLC) is an area that is
critical to many industrial sectors, and in particular, within the
defense and aerospace where products are complex and have extended
life cycles. One of the key problems in modeling the cost
of these products is the limited life-cycle information at the early
stage. This leads to epistemic and aleatory uncertainty within the
estimation process in terms of data, estimation techniques, and
scenarios analysis. This paper presents a review of the uncertainty
classification in engineering literature and the nature of uncertainty
in TLC estimation. Based on the review, the paper then
presents a critique of the current uncertaintymodeling approaches
in cost estimation and concludes with suggestion for the requirement
of a different approach to handling uncertainty in TLC. The
potential value of imprecise probability should be explored within
the domain of TLC to assist cost estimators and decision makers
in understanding and assessing the uncertainty. The implication of
such a representation in terms of decision making under risk and
decision making under uncertainty is also discussed
Using Taguchi to optimise performance and product cost at the conceptual stage of design
The difficulty of obtaining a useful cost estimate at the design
stage has long been acknowledged. Data for new products is hardly
available and product specifications are often expressed as a range of
values yet, only limited progress has been made to date to improve the
quality of the average cost estimate at the conceptual design stage. The
aim of this research is to improve the quality of the cost estimate
(average cost) at the conceptual stage of design to assist designers to
consider cost as a critical factor in selecting the most appropriate design
concept. This research investigates the use of Taguchi’s orthogonal array
approach to reduce the variation in the product specification (when
expressed as a range of values) in order to improve the quality of the
average estimated cost for each concept at the conceptual stage of design.
A new process has been created and to validate the process, an industrial
case study has been undertaken
A framework for considering uncertainty in quantitative life cycle cost estimation
Life Cycle Cost (LCC) is important information that is useful for decision making affecting complex engineering systems with extended life. Uncertainty in the estimation of LCC, especially in the early concept and definition stage, has great influence on the robustness of such decisions. Conventionally, Verification and Validation (V&V) of cost estimates is not performed, either due to economic or practical constraints. This paper presents a framework for considering uncertainties in quantitative life cycle cost estimation, focusing on the aspects that are important for understanding the discrepancies between the estimated and actual costs. Built on experience in verification and validation in engineering, the framework will be used to guide further research in this topic, where emphasis on suitable theories and models of different types of uncertainties in the estimation as well as strategies to deal with them effectively to improve decision making involving LCC will be discussed