scholarly journals The Need for Systems Awareness to Support Early-Phase Decision-Making—A Study from the Norwegian Energy Industry

Systems ◽  
2021 ◽  
Vol 9 (3) ◽  
pp. 47
Author(s):  
Siv Engen ◽  
Kristin Falk ◽  
Gerrit Muller
Keyword(s):  
Decision Making ◽  
Early Phase ◽  
Energy Industry ◽  
Engineering Systems ◽  
Concept Evaluation ◽  
Depth Study ◽  
Complex Engineering ◽  
Complex Engineering Systems

In this paper, we explore the need to improve systems awareness to support early-phase decision-making. This research uses the Norwegian energy industry as context. This industry deals with highly complex engineering systems that shall operate remotely for 25+ years. Through an in-depth study in a systems supplier company, we find that engineers are not sufficiently aware of the systems operational context and do not focus on the context in the early phase. We identified the lack of a holistic mindset and the challenge of balancing internal strategy and customers’ needs as the prevalent barriers. To support the concept evaluation, the subsea system suppliers need to raise systems awareness in the early phase. The study identifies four aspects that are important to consider when developing and implementing approaches to improve systems awareness in the early phase.

A Framework for Considering Uncertainty in Quantitative Life Cycle Cost Estimation

2009 ◽  
Author(s):  
Yee Mey Goh ◽  
Linda Newnes ◽  
Chris McMahon ◽  
Antony Mileham ◽  
Christiaan J. J. Paredis
Keyword(s):  
Decision Making ◽  
Life Cycle ◽  
Cost Estimation ◽  
Life Cycle Cost ◽  
Great Influence ◽  
Verification And Validation ◽  
Engineering Systems ◽  
Complex Engineering ◽  
Complex Engineering Systems ◽  
Practical Constraints

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.

Effectiveness Of Life Cycle Management Of Projects Using Information Modeling

2019 ◽  
pp. 24-29 ◽  
Keyword(s):  
Life Cycle ◽  
Construction Projects ◽  
Life Cycle Management ◽  
Information Modeling ◽  
Engineering Systems ◽  
Basic Principles ◽  
Complex Engineering ◽  
Domestic Practices ◽  
Capital Construction ◽  
Complex Engineering Systems

Improving the efficiency of life cycle management of capital construction projects using information modeling technologies is one of the important tasks of the construction industry. The paper presents an analysis of accumulated domestic practices, including the legal and regulatory framework, assessing the effectiveness of managing the implementation of investment construction projects and of complex and serial capital construction projects, as well as the life cycle management of especially dangerous technically complex and unique capital construction projects using information modeling technologies, especially capital construction projects, as well as their supporting and using systems, primarily in the nuclear and transport sectors. A review of modern approaches to assessing the effectiveness of life cycle management systems of complex engineering systems in relation to capital construction projects is carried out. The presented material will make it possible to formulate the basic principles and prospects of applying approaches to assessing the effectiveness of the life cycle management system of a capital construction project using information modeling technologies.

Design of Complex Engineering Systems Using Multiagent Coordination

2016 ◽  
Author(s):  
Nicolás F. Soria ◽  
Mitchell K. Colby ◽  
Irem Y. Tumer ◽  
Christopher Hoyle ◽  
Kagan Tumer
Keyword(s):  
Autonomous Agents ◽  
Engineering Systems ◽  
Coordination Problem ◽  
Design Decisions ◽  
Multiagent Coordination ◽  
Trade Offs ◽  
Potential System ◽  
Complex Engineering ◽  
System States ◽  
Complex Engineering Systems

In complex engineering systems, complexity may arise by design, or as a by-product of the system’s operation. In either case, the root cause of complexity is the same: the unpredictable manner in which interactions among components modify system behavior. Traditionally, two different approaches are used to handle such complexity: (i) a centralized design approach where the impacts of all potential system states and behaviors resulting from design decisions must be accurately modeled; and (ii) an approach based on externally legislating design decisions, which avoid such difficulties, but at the cost of expensive external mechanisms to determine trade-offs among competing design decisions. Our approach is a hybrid of the two approaches, providing a method in which decisions can be reconciled without the need for either detailed interaction models or external mechanisms. A key insight of this approach is that complex system design, undertaken with respect to a variety of design objectives, is fundamentally similar to the multiagent coordination problem, where component decisions and their interactions lead to global behavior. The design of a race car is used as the case study. The results of this paper demonstrate that a team of autonomous agents using a cooperative coevolutionary algorithm can effectively design a Formula racing vehicle.

A technique to assess the changeability of complex engineering systems

2013 ◽  
Vol 24 (7) ◽  
pp. 477-498 ◽  
Author(s):  
Edwin C.Y. Koh ◽  
Nicholas H.M. Caldwell ◽  
P. John Clarkson
Keyword(s):  
Engineering Systems ◽  
Complex Engineering ◽  
Complex Engineering Systems
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