Multi-attribute analysis

Multi-attribute utility (MAU) analysis [5] is a powerful tool accounting for many other criteria and constraints, besides costs, involved in the technol­ogy selection process. MAU analysis is an effective and efficient way of showing the impact of each technology option in terms of good practice attributes, and of reaching conclusions that address all of the influencing factors. Such analysis involves assigning numerical ratings and weightings to the factors considered, followed by comparison of the obtained total scores for the options. If necessary (i. e., when two options have very close scores), a sensitivity analysis can be performed to check whether or not the preferred option is the right choice. A simple scoring of the criteria for a given option allows any option to be discarded or considered for further evaluation. Regardless of the approach it is necessary to produce a justifi­able and auditable solution for selected options.

Table 4.1 Technology-related criteria and attributes




Good practice attributes


1 National policy and strategies


Compliance with the intent of national polices and strategies. In the case of insufficient national policies and strategies, compliance with international ‘good practice’.

Compliance with the requirements of the regulatory framework. In the case of insufficient regulatory framework, compliance with international ‘good practice’. Clearance levels are set up. Mechanism for authorized discharge is established.

Both direct and indirect costs (e. g., stakeholder involvement and public acceptance) addressed. Total cost of the viable technology evaluated or compared and technology selected/eliminated in terms of main cost factors. Adequate financial resources or financial security and funding mechanisms available for the funding of viable technology.

HSE impacts of viable technologies known and considered in the selection of technologies; HSE impact optimized by reducing exposure of the workforce and members of the public. The need for transportation of radioactive material is minimized.

Identification of all sources of waste generation. Waste characterization developed and can be implemented at all stages of the waste management process.

Waste management system exists and can support the newly introduced technology. Storage/disposal facilities available. Operational waste generation control programme in place.

Availability of suitably qualified and experienced personnel. Consideration of lessons learned from implementation of other technologies. Technologies discussed with stakeholders and considered in a transparent way. All stakeholders involved in the selection of a technology and reasonable consensus reached. All technical factors affecting the selection of a technology (e. g., maturity, robustness, complexity and maintainability, etc.) are taken into account.

Physical structure is available and can support the newly introduced technology.


2 Regulatory framework


3 Funding and cost


4 Health, safety and environmental (HSE) impact


5 Waste



6 Waste management system

7 Human resources


8 Social impacts and stakeholder involvement

9 Technical factors


10 Physical





4.2 Linear decision-tree approach for the technology selection of a waste stream.


The MAU method makes clear to all involved the basis on which the alternatives are being evaluated. It offers quantifiable principles for choos­ing options. This is particularly important in group decision-making situa­tions, in which many different points of view and alternative decisions have to be reviewed and taken into account. The attributes needed for evaluation of options must be identified. They are assigned a weight that reflects their importance to the decision. A value of 3, 2 or 1 might be assigned to each attribute, depending on its importance. Alternatively 100 points can be assigned and distributed over the attributes according to their importance. A score can be given to each of the alternatives for each attribute. A scale of 1-10 may be used. The score of each alternative for each attribute is then multiplied by the weight of that attribute, and the total is calculated. That total represents the value of that option, which can then be compared to the same calculation for the other options. If it is a group process, each member of the group scores the attributes for each option and the group’s ratings can be totalled or averaged. The final result of this example analysis would be a relative, numerical ranking of the options (the score for each option).

Furthermore, various criteria such as non-safety-related matters could also be considered in the process of selecting an option. Where relevant, safeguard-related issues should also be considered in optimizing both safety and resources in the decision-making process. The costs of maintenance, surveillance and physical protection for the waste management facility should also be taken into account. It should be ensured that the selected option meets all the applicable safety requirements. A MAU model can be used to further explore the consequences of changing the attributes, their weights, or the scores they received. Since the criteria are transparent, it is possible to make several changes and review the results. For example, if it appears that some attributes are too important in determining the results, the weights could be adjusted to produce more realistic results.

Workshop sessions (sometimes called brainstorming sessions or decision conferences) can provide a practical and motivating way forward. In such sessions a panel of relevant experts (including experienced operators) agree on the list of influencing factors and then assess the impact of these factors on each of the technological options, assisted by the use of decision-aiding techniques. It is important to produce a report of the workshop sessions, describing the technique adopted, the considerations addressed and the results obtained. This report can be a valuable aid in support of the waste management plan and the associated safety justification.

The processes of selecting a preferred technology and the subsequent detailed strategy are best approached by ensuring that the team clearly understands the underlying safety logic. This logic must be applied to each of the candidate options (at an appropriate level of detail), as part of the process of selecting a preferred option. The key point is to ensure that there is a demonstrable connection between the characteristics and amounts of radioactive waste at generation, the proposed technologies, the associated risks in implementing these technologies, the safety management arrange­ments, and costs. For example, analysis of the risks involved logically deter­mines the requirements for key aspects such as additional or modified equipment, staff training, procedures, work instructions, maintenance and security arrangements.

4.5 Conclusion

Before embarking on the selection of a particular technology or selection of options to address complex waste management needs, it is essential to analyse the waste generation thoroughly and understand the properties, types and volumes of waste. It is necessary to fully comply with the regula­tory regime, and to ensure that disposal options are available. It is assumed that legal and regulatory infrastructure related to waste management exists or is going to be established as soon as practicable. The selection of a tech — nology/technical option needs then to be based on the evaluation of all relevant criteria and constraints.

More details on this topic will be provided in a forthcoming IAEA pub­lication that is tentatively titled ‘Selection of Technical Solutions for the Management of Radioactive Waste’.

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