Use Cases for AI in Reliability and Maintainability

This paper explores writing a use case for applying AI to support asset reliability and maintainability. The primary concentration is on establishing a system description, defining actors, and outlining objectives. Use cases when applied in systems engineering or other contexts are a valuable tool for describing with clarity the different ways actors (i.e., users) will interact with a system and what constitutes success resulting from those interactions. AI is a complex technology requiring subject matter experts in the field. Most organizations will not have sufficient capability to apply AI without some outside assistance. It is unrealistic to assume that outside assistance, though skilled in AI, will have a working knowledge of your industry. A use case brings together the skill and knowledge of AI experts with the skill and knowledge of your organization and its operations into a common framework. Writing a use case is a multistep process. System function and system interaction are logically connected. Use cases applied to complex systems will be hierarchical to mirror those connections. This results in a compilation of use cases at multiple levels and with connections to multiple actors. Each actor typically has multiple objectives, some common with other actors and some unique to individual actors. Objectives are often intertwined with multiple linkages across different actors. In most organizations that use assets to provide a product, service, or perform a mission there are groups and departments with specific focus areas that relate to each other but do not have a detailed understanding of what each other do and what it take to be successful. Exploring all the steps of writing a use case for applying AI in R&M will require more writing space and time than the constraints of this paper and conference will allow. The exploration will be confined to the first three steps: 1) system description; 2) identifying actors; and 3) defining the goals and objectives for each actor. These three steps are foundational in uncovering the information needed to outline all the ways in which AI can provide valuable capability to enhance use of R&M data to elevate an organization's performance. Reliability and Maintainability (R&M) touches all aspects of management, operations, and maintenance in organizations that use physical assets to produce products, provide services, or perform missions. Asset reliability is needed for operations to perform their function. It is also the purpose of maintenance to sustain and restore reliability efficiently so downtime is minimized. Finally, management needs asset reliability to meet the organization's commitments and realize success. R&M is a data driven undertaking. AI is a major turning point in all technical fields going beyond what is considered evolutionary progress into what most will agree is a true revolution in how data can be used in detecting, defining, and clarify problems then ultimately deriving and evaluating solutions. Making the effort to compile use cases for all the actors (any group within the organization who will interact with the AI technology or its outcome) prior to stepping into an arrangement with AI professionals to implement AI in your organization will increase probability of success. It is the simplest and oldest intention when communicating between individuals or groups to clearly state in easy-to-understand terms what is expected and what is the end goal. The use case is purposefully designed as a means for the provider to understand what the customer expects.