In today’s world, the crews that maintain and upgrade utility infrastructures are busier than ever. They typically operate over a wide geography, which inevitably leads to travel time. But travel time is isn’t “wrench time,” so anything that can help utilities optimize scheduling can really improve the efficiency and effectiveness of their crews.

One of the best approaches is exception-based scheduling or, as it’s sometimes called, rule-based automated scheduling or alert-based scheduling. Exception-based scheduling requires integrating an enterprise work-management system with an enterprise scheduling system to intelligently automate and optimize the process of schedule optimization. This approach makes it possible to reduce travel time, stay compliant with fatigue-management policies, and be flexible enough to handle last-minute problems.

Many work and asset management systems as well as scheduling systems have overlapping functions and utilities that make it difficult to establish ownership of process and data. With deep experience in implementing end-to-end solutions for work management and scheduling systems, Wipro can help utilities kick-start business transformations with a predefined process and data ownership templates across systems. This helps utilities reduce the implementation time and lower the total cost of ownership of such transformations.

How It Works

The cornerstone of an exception-based scheduling solution is a fully automated system that matches demand with scheduling constraints for approval by the utility’s scheduling or planning team. The system uses a rules engine so that routine requests are fully automated, and exceptions or tasks that cannot be automatically scheduled are called out and communicated via notifications.

The utility’s enterprise asset management (EAM) system forecasts the work. Calendar-based preventative maintenance tasks – such as scheduled line inspections or transformer oil collections – are very simple to forecast. For runtime-based maintenance tasks, historical run-hours can be used

Figure 1: Work forecast and capacity demand view

for forecasting; a good example would be how many times a relay has operated. Corrective and emergency work can be forecast using historical data.

Forecast projects would include the following data points:

• Work order: Descriptive text about the work to be done (e.g., transformer oil sample collection)
• Schedule window: A time window for when the work should be performed
• Crew/skills: Type of crew required
• Duration for which crew will be required to complete the work
• Work dependencies on any other work order.
• Other dependencies on non-work activities (e.g., backordered materials)

Scheduling Rules

After the EAM system has forecast the work, the tasks are moved to the scheduling system, which needs well-defined rules in order to create an optimized schedule. Some typical examples: 

• Who works when: Shift patterns, planned time off
• Fatigue policies: Many utilities have guidelines about how long a person should work on hot wires or rules about scheduling jobs once travel time reaches a certain level.
• Geo restriction policies: Utilities may prohibit deployment for jobs that are more than 50 miles from a worker’s base. 

There will always be more than one way to plan the work, and it’s not always possible to create a schedule that adheres to all the known constraints. That’s why it’s critical to establish well-defined rules outlining constraints, priorities, and “must haves.” 

Capacity Planning and Resource Levelling 

Armed with a work forecast and team availability, the exception-based scheduling system matches available capacity against the demands by crew skills and times when the skills are required. The capacity view (an example is shown in Figure 2) can help planners anticipate possible gaps in capacity and take action to optimize schedules. Work orders can be moved around the timeline to adjust demands within the available capacity. 

Figure 2: Capacity vs demand view

Managing Exceptions

With this groundwork in place – defined work/activities, personnel and compliance constraints, and capacity planning – the system is enabled to perform exception-based scheduling. That is valuable in itself, but the system can go further, enabling planners to use key result areas (KRAs) and key performance indicators (KPIs) to ensure they are truly optimizing scheduling. Typical metrics might include maximizing in-house maintenance, outsourcing low-priority work, and minimum spends on a crafts/hour basis.

Next Steps

The key benefit of adopting an intelligent, rules-based or exception-based scheduling solution is automation. The system can create effective, efficient plans with great flexibility and latitude to help prepare for the inevitable. Perhaps more important, automating a substantial part of the scheduling function enables planners and schedulers to focus on higher-value activities.

To build and implement rule-based scheduling system is a journey, not a one-step improvement. Different organizations will be at different levels of maturity as they undertake this journey. Wipro can help utilities understand their current maturity state and establish a roadmap for implementing state-of-the-art and future-ready scheduling systems.

In order to embark on journey of modernizing the scheduling function, any organization have work and asset management and schedule management functions implemented and operational. The scheduling parameters should be documented (not necessarily automated). Once those functions are in place organization is ready to leap forward to scale the scheduling business function to the next level.  For more details, please visit https://www.wipro.com/utilities/.