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ENGINEERING PROJECT RISK MANAGEMENT MODEL
Open accessAbstract
This article investigates a comprehensive approach to developing risk management models for engineering and IT projects by integrating standardized methodologies–defined by ISO 31000 and the PMI PMBOK Guide–with modern digital analytical tools. The growing complexity of project environments, rapid technological shifts, and increased systemic uncertainty highlight the urgent need for advanced methods capable of enhancing the accuracy and speed of risk assessment. The study proposes a structured framework that includes the identification, categorization, and both qualitative and quantitative evaluation of risks using a Risk Breakdown Structure (RBS), a probability–impact matrix, and scenario-based analytical techniques such as Bow-tie modelling, Fault Tree Analysis (FTA), and Decision Tree analysis. Particular emphasis is placed on the potential of artificial intelligence–specifically generative models–to support automated diagnostics and reduce subjectivity in expert-based evaluations. As part of the research, a software prototype titled "Risk-App" was developed to demonstrate the integration of the GPT-API into the risk management workflow. The prototype provides automated risk identification, threat classification, and the generation of response recommendations to support the selection of optimal mitigation strategies. The results indicate that combining traditional risk management practices with intelligent computational tools significantly increases decision-making effectiveness and improves project resilience under multifactor uncertainty. The study concludes that AI-enhanced risk management systems can substantially expand analytical capabilities, accelerate the evaluation process, and improve overall project outcomes by providing real-time, data-driven insights.
Overview
CoChat Summary
TL;DR
The paper develops a risk-management model for engineering projects that combines ISO 31000:2018 and PMI PMBOK (7th ed.) with structured tools (RBS, probability × impact matrix, Bow-tie, FTA, Decision Tree) and a GPT-API-based software prototype, Risk-App. It argues the integrated approach formalizes risk identification and assessment and reduces subjectivity in expert judgments.
Key findings
- A combined ISO 31000:2018 + PMBOK framework is proposed to give unified analysis procedures, multi-level risk models, digital-tool integration, and better-grounded management decisions in engineering and IT projects.
- Risk Breakdown Structure (RBS) is used to classify risks into technical, organizational, external, managerial, financial, and personnel categories, structuring identification and reducing the chance of missing critical factors.
- The probability × impact matrix serves as an initial filter that sorts risks into low, medium, or high criticality zones, after which Bow-tie, FTA (with AND/OR boolean operators), and Decision Tree methods support deeper scenario analysis.
- The Risk-App prototype integrates GPT-API via prompt engineering (system instructions, user data, format templates, iterative refinement including chain-of-thought) to auto-generate RBS, scenarios, consequences, and response options; Table 1 illustrates five example risks (e.g., design error — medium probability, high impact, high criticality, minimization; supply delays — high/high/high, minimization).
Methods
- Conceptual/design study: the authors analyze ISO 31000:2018 and PMI PMBOK Guide (7th ed.) and synthesize them into a risk-management model for engineering projects.
- Tool development: construction of an RBS hierarchy, a probability × impact matrix, and scenario-analysis methods (Bow-tie, FTA, Decision Tree), plus a software prototype (Risk-App) with GPT-API integration and prompt-engineering workflow.
- Illustration: a single example table of Risk-App output (five risk categories with cause, probability, impact, criticality, and recommended strategy); no sample, dataset, or statistical analysis is reported.
Limitations
- Stated by the paper: further work is needed to add quantitative analysis and forecasting methods, sensitivity-analysis tools, simulation (e.g., Monte Carlo), adaptation to different engineering/IT/manufacturing project types, and model training on domain-specific datasets — implying the current prototype lacks these.
- Evident from the text: the "approbation" results are asserted but no empirical validation, sample, case project, or performance metrics are reported; the only concrete output is a five-row illustrative table, so claims about reduced subjectivity and improved accuracy are not empirically demonstrated.
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Verification
Claims the paper makes
0 Valid · 0 Not valid · 16 Not checked · 18 Own results and interpretations
In the paper
“3) мінімізувати ймовірність пропуску критичних чинників завдяки системному охопленню потенційних джерел ризику;”
What the sources say
- Not matchedcites [4]
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plainstates a cause- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Not matched
In the paper
“4) забезпечити узгодженість між аналітиками, експертами й менеджерами, оскільки RBS створює спільну термінологічну та логічну основу для аналізу [4].”
What the sources say
- Not matchedcites [4]
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plainstates a cause- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Not matched
In the paper
“Цей інструмент є базовим елементом системи ризик-менеджменту відповідно до стандартів ISO та PMBOK, оскільки дає змогу оперативно структурувати ризики, визначити їх пріоритетність та сформувати основу для планування заходів реагування.”
What the sources say
- Not matchedcites [7]
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plainstates a cause- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Not matched
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“У результаті було сформовано комплексний методологічний підхід до управління ризиками інжинірингових проєктів, що інтегрує положення міжнародного стандарту ISO 31000:2018 та принципи PMI PMBOK із сучасними засобами цифрової аналітики та штучного інтелекту.”
plainstates a cause- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Завдяки їх поєднанню було отримано комплексне бачення механізмів виникнення ризиків та можливостей їхнього контролю на різних рівнях системи.”
plainstates a cause- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
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Citations
Cites
Still being checked.
Research works printed but not linked: 7
- Черненко, Ю., Бородін, Б. (2025). Моделювання проєктних ризиків для сталої господарської діяльності компанії. Сталий розвиток економіки, 1 (52), 382-386.
- Chernenko, YU., Borodin, B. (2025). Modelyuvannya proyektnykh ryzykiv dlya staloyi hospodarsʹkoyi diyalʹnosti kompaniyi [Modeling project risks for sustainable economic activity of the company]. Stalyy rozvytok ekonomiky [Sustainable Development of Economy], 1 (52), 382-386. [in Ukrainian].
- Ericson, C. A. (2005). Fault tree analysis primer. Wiley.
- Hillson, D. (2002). The risk breakdown structure (RBS) as an aid to effective risk management. International Journal of Project Management, 20(5), 337-345.
- Lytvynenko, D., Malyeyeva, O. (2022) Управління ризиками в проєктах відновлення транспортної інфраструктури регіону на основі комунікацій учасників. Сучасний стан наукових досліджень та технологій в промисловості, 2 (20), 44-51.
- Lytvynenko, D. & Malyeyeva, O. (2022) Upravlinnya ryzykamy v proyektakh vidnovlennya transportnoyi infrastruktury rehionu na osnovi komunikatsiy uchasnykiv [Risk management in regional transport infrastructure restoration projects based on participant communications]. Suchasnyy stan naukovykh doslidzhenʹ ta tekhnolohiy v promyslovosti [Current status of scientific research and technologies in industry], 2 (20), 44-51. [in Ukrainian].
- Project Management Institute. (2021). A guide to the project management body of knowledge (PMBOK® Guide) (7th ed.). PMI.
Cited by
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Metadata
- Authors
- Novoseletskyy, O., & Bondarchuk, V.
- Affiliations
- National University Ostroh Academy (UA)
- Venue
- Scientific Notes of Ostroh Academy National University, "Economics" Series
- Published
- 2025-12-18
- Volume
- 1
- Issue
- 39(67)
- Pages
- 231-235
- ISSN
- 2311-5149 (ISSN-L)
- OpenAlex
- W7128715633
- Semantic Scholar
- 2d09f8275dba39644e42fd7222470785eee08b28
- Cited by
- 0
- References
- 0
- FWCI
- 0.00
- Type
- journal article
- Language
- en
- Open access
- diamond
- doi.org
- Locations
- Scientific Notes of Ostroh Academy National University Series Economics (publishedVersion)
- Digital Repository of Ostroh Academy (Ostroh Academy) (acceptedVersion)
- Topics
- Social Sciences › Decision Sciences › Management Science and Operations Research › Construction Project Management and Performance
- Social Sciences › Business, Management and Accounting › Management of Technology and Innovation › Economic and Technological Systems Analysis
- Social Sciences › Economics, Econometrics and Finance › Finance › Capital Investment and Risk Analysis
- Keywords
- project risk management, engineering projects, IT projects, ISO 31000, PMBOK Guide, risk breakdown structure, probability-impact matrix, fault tree analysis, decision tree analysis, generative AI, risk mitigation strategies, project resilience
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