Modeling Maintenance Processing

The corrective maintenance process is divided into the following steps:

1. Create notification

Malfunctions and other requirements are recorded in a notification based on technical object (= reference object).

2. Plan maintenance order

In this step, orders are created and planned based on the reported requirements. Planning encompasses the steps to be taken, the material required, and any PRTs.

3. Check and release maintenance order

In this step, the order runs through different checks (such as material availability checks and capacity planning) which are important for the release of the order. The system checks whether permits need to be approved, safety plans are required and if the work clearance requirements for certain areas are fulfilled.

If no problems arise during these checks, the order is put in process. The shop papers are usually printed at this point.

4. Execute maintenance order

The order is executed in this step. The required material for the order is withdrawn. This includes material that has not been planned, and therefore not reserved, by the order.

5. Confirm maintenance order

During this step, time confirmations (for maintenance order) and technical confirmations (for notification) are entered in the system.

6. Complete maintenance order

In this step, the order is set to technically complete. The settlement of the order is carried out by Controlling (CO). Finally, the maintenance order is set to business complete.

The phase model is available for the following processes / scope items:

• Proactive Maintenance (4HI)
• Reactive Maintenance (4HH)
• Improvement Maintenance (4VT)
• Operational and Overhead Maintenance (4WM)

1. Initiation

During this phase, you submit a maintenance request, view the details of all the maintenance requests you submitted and prioritize maintenance events.

2. Screening

During this phase, you can review the submitted maintenance requests and see whether the required information is complete.

3. Planning

After the maintenance request has been accepted, you can start planning the resources for the maintenance order. This order inherits the data of the accepted maintenance request.

4. Approval

Maintenance orders will be approved using a flexible workflow process. Approved orders can be released.

5. Preparation

Once the order has been released, the maintenance planner divides the maintenance effort into manageable groups, levels out the work load over several weeks, determines the concrete time period for the requested maintenance work and checks the availability of all the required resources, spare parts and services.

6. Scheduling

During this phase the maintenance planner or scheduler dispatches the order operations and suboperations and thereby confirms that they have been scheduled at the right work center and at the right time.

7. Execution

During this phase, the maintenance technician executes the preliminary and main maintenance tasks.

8. Post Execution

During this phase, the maintenance technician documents time and material consumption.

9. Completion

During this phase, the maintenance planner or financial controller reviews maintenance orders that have already been technically completed but not yet financially settled, performs all the necessary tasks and finally sets the orders to Complete (Business).

The phase-based process can be shortened by using the processing context for notifications which initiates two exception processes:

• Emergency Work

  The notification will not be screened an is automatically accepted. An order is automatically created and approved in the background.

• Minor Work

  This involves only a notification (without order) with no need to screen or accept. All necessary steps are done within the notification.

This process is carried out via Fiori Apps Report and Repair Malfunction. The most striking feature in this process is the fact that all steps are processed within a single app (if executed without interruption).

1. Notification & Order

Via Report Malfunction a notification is created - together with an order in the background.

2. Plan Work

You can plan operations with work and material within the same app.

3. Release and Execute

After releasing the order it is executed. Reserved material will be withdrawn by the warehouse clerk.

4. Confirm and Document

When work is finished times, damage codes, causes and activities are recorded.

5. Complete

After recording all times and activities order and notification are completed.

There are different types of artificial intelligence (AI) available:

• Generative AI

  generates new content in different formats

• Traditional AI

  refers to AI systems that can perform specific tasks by following predetermined rules or algorithms.

• Machine Learning

  enables a system to learn from data rather than through explicit programming.

• Conversational AI

  enables machines to understand and respond to human language in a human-like manner.

• Artificial General Intelligence (AGI)

  refers to highly autonomous systems – currently hypothetical – that can outperform humans at most economically valuable work.

• Predictive AI

  refers to the use of machine learning to identify patterns in past events and make predictions

Joule is an AI copilot that’s grounded in your business data and infused with AI agents to proactively assist your employees in every cloud application they use while automating complex processes. Joule offers both Informational and Transactional Capabilities. The informational capability of Joule allows you to search and analyze the information available on f.ex. the SAP Help Portal. The transactional capability of Joule allows you to complete business tasks by interacting with Joule in a natural and intuitive way.

For example, you can ask Joule to display business objects using natural language in SAP S/4HANA Cloud Public Edition for Asset Management:

• Work Center
• Maintenance Order
• Material
• Bill of Material

Examples for AI functions in Asset Management:

When you create a maintenance order for a notification, you can leverage machine learning capabilities of SAP AI Services to find suitable orders from which you can copy information based on historical data in your system.

By analyzing the description as well as other important attributes of the selected notification and its reference object, the machine learning algorithm is able to identify and recommend orders that have been created for similar notifications in the past.

As a maintenance planner, you can review the recommended orders and select the most suitable one as a reference template for the new maintenance order.

This feature is available in the Manage Maintenance Notifications and Orders app (F4604) within SAP S/4HANA Cloud Private Edition.

With this feature, you can identify suitable task lists for maintenance orders using data captured in maintenance items. Maintenance items provide an easy way to link a single task list with different pieces of equipment, functional locations, or materials. You can also specify reasons to describe when that task list could be used to resolve issues with these objects.

To help you create order descriptions that match existing reason short texts, this feature includes a type-ahead search in the Description field of maintenance notifications and orders. This functionality searches for similar reason short texts as you type the problem description, allowing you to describe similar issues consistently and increasing the success rate of the task list search.

This function is available in SAP GUI transactions IW21, IW22, IW31, and IW32 and needs to be activated in Customizing.