Tony Rosqvist

Value-driven maintenance planning for a production plant

Maintenance involves maintaining and securing the equipment and systems in, or restoring them to, a state in which they can perform the required functions. The challenge for maintenance planning is to identify appropriate objects and tasks for preventive maintenance and ensure that there are adequate resources for the repair actions. In this paper we will present a maintenance planning approach, called value-driven maintenance planning (VDMP), to emphasise the fact that the objectives of the plant are the reference points for specifying functional requirements for the equipment locations and equipment.

Qualification of Formal Safety Assessment: an exploratory study

Abstract Formal Safety Assessment (FSA) is an approach adopted by the International Maritime Organisation (IMO) to support a systemic and structured assessment of proposals for new international regulations to improve shipping safety. Several case studies based on the approach have been conducted during recent years. This paper addresses the issue of confidence in a FSA, as encountered during three case studies conducted by the authors over the years 1998–2002. A peer review process—FSA qualification—is introduced to support the consolidation of confidence in FSA results. Some qualification criteria are suggested.

Bayesian aggregation of experts' judgements on failure intensity

Abstract Predictive modelling in the field of dependability, such as repair cost modelling, is usually based on the failure intensity function of repairable systems. The experience feedback data needed to estimate the failure intensity function is, however, seldom available due to the unique character of the systems. Thus approaches that can capture the tacit knowledge of designers, operators and maintenance personnel and transform this to the mathematical format required in the predictive models, are needed. A Bayesian statistical approach is presented, which yields posterior distributions of the parameters of the Power Law and the Log-Linear intensity functions, which are used to model the trend in the data observed. Model-checking criteria are presented according to which the relative performance of the selected functions can be assessed. Numerical examples are also given.

On the validation of risk analysis: A commentary

Abstract Aven and Heide (2009) [1] provided interesting views on the reliability and validation of risk analysis. The four validation criteria presented are contrasted with modelling features related to the relative frequency—based and Bayesian approaches to risk analysis. In this commentary I would like to bring forth some issues on validation that partly confirm and partly suggest changes in the interpretation of the introduced validation criteria—especially, in the context of low probability–high consequence systems. The mental model of an expert in assessing probabilities is argued to be a key notion in understanding the validation of a risk analysis.

Multi-criteria decision analysis in adaptation decision-making: a flood case study in Finland

Decision-making for the purpose of adaptation to climate change typically involves multiple stakeholders, regions and sectors as well as multiple objectives related to the use of resources and perceived benefits. Standard cost–benefit analysis can be argued to take into account easily monetised effects only. Multi-criteria decision analysis (MCDA) embedded in participatory processes can therefore play an important role in defining the decision context and exploring stakeholders’ preferences. In this paper, a case study on flood protection of the Kokemäki river running through the city of Pori in West Finland was conducted. The study was realised as a MCDA workshop involving the key stakeholders of the region. The analysis produced a robust ranking of the considered flood protection alternatives. According to the stakeholders, the approach was useful as an exploratory way of gaining a deeper and shared understanding of the flood protection. It was shown that MCDA is well suited for decision-making in adaptation to climate change–enhanced extreme events.

Dynamic Project Portfolio Selection in Infrastructure Sector

Infrastructure networks are vital to the national economy. Their Asset Management (AM) should result in long-term economic efficiency and optimal service levels. For AM to live up to the expectations of infrastructure sector, it has to meet four key challenges: 1) alignment of strategy and operations with stakeholder values and objectives; 2) balancing of reliability, service-level, safety, and financial considerations; 3) ensuring optimal packaging and timing of works, and adequate competition; and 4) promoting market development. Through educated decision-making, asset managers can actively develop their networks and use their limited budgets in a way that long-term goals and short-term budgets are met. In order to assist asset managers, a simplified Project Portfolio Selection Method (PPSM) is developed. The method applies the analytical hierarchy process (AHP) and real option ideology. PPSM aims at assisting infrastructure managers in optimising the life cycle profiles of their assets through selection of an optimal maintenance, repair and rehabilitation project portfolio. The developed method fills the void between strategic and operative decision-making methods facilitating management of multiple investments at the local network management level. Through the systematic, easy-to-apply project selection method, the asset manager can easily determine the optimal project portfolio and demonstrate the grounds to others.

Capacity Investment Planning Based on Real Options

Capacity management of a plant in capital-intensive industries is a challenging task: volatile markets, aging and deteriorating equipment and a competitive environment raise challenges for capacity management. Essentially, capacity management is decision-making under uncertainty at the plant-level. Risk-informed, dynamic, capacity management is a prerequisite for achieving optimal capacity in a production plant. One way to deal with uncertainty is the active management of real options. Investment portfolios consisting of real options provide opportunistic value in capacity investment decision-making. A framework for the specification, evaluation and exercising of real options is presented for capacity managers. The analysis is based on a decision cycle which is temporally divided into two market outlook periods. The first market outlook period represents the current, emerging market situation for which real options, planned in the previous decision cycle, may be exercised, thus optimising production capacity according to current demand. The second period represents an uncertain production environment for which real options can be planned, based on demand & supply forecasts. The decision cycles repeat, each entailing planning, evaluation and exercising of real options included in the investment portfolio. The framework supports the computation of the probability distribution of profits coupled with alternative investment portfolios. The paper introduces a straightforward way of adopting options theory in the context of real options in capacity management.

Assessing the subjective added value of value nets: Which network strategies are really win-win?

As manufacturing companies increasingly focus on their core business, the interest in the utilisation of external services provided by system suppliers and service companies increases. Currently an increasing number of services are purchased from service supply networks. Furthermore, globalisation, complexity of technological innovations and demand for integrated solutions also create need for networking and collaboration. Establishing or improving the performance of the networked service providers, the value net, is a long-term effort, requiring the build up of trust between the partners. The necessary condition of moving from a subcontractor relationship to a strategic network or partnership is the sharing of the view of joint gains in a prospective value net. How do we then evaluate the added value of moving to a new partnership? What network strategies provide the win-win network solution? This paper is a tentative effort in answering these questions based on Decision Analysis.

Precautionary Risk Decision-Making

Uncertainties related to a risk assessment significantly affect the confidence in the risk results and recommendations obtained. Uncertainties are dependent on the complexity and understanding of the causal and/or logical relationships of quantities and/or events of the real world, and their roles in the decision-making process depend on the adopted decision rules and criteria.

Assessing climate change adaptation strategies—the case of drought and heat wave in the French nuclear sector

Nuclear energy is a very important component of overall power supply in France. If the effects of future extreme weather events or climate shifts are not addressed, energy systems will be highly vulnerable to extreme weather events or shifts in weather patterns, such as changes in precipitation. Because of the deep uncertainties involved in climate projections and response strategies, any strategy implementation should perform adequately regardless of which scenario actually materialises. In this paper, we analyse the effects of drought and heat wave in the French nuclear energy sector using the Strategy Robustness Visualisation Method. The key feature of the method is the modelling of uncertainty of the quantitative indicators by (min, max) values plotted on radar plots such that each strategy option’s performance can be visually inspected for robustness. The method can be utilised as a “module” of its own in different uncertainty management approaches. Based on the case study, the presented adaptation strategies “Maintaining industrial production and final demand” and “Smart grid infrastructure” were more robust than the “No planned or automatic adaptation”.