How to mass close work orders based on saved searc...
# ask-stanley-ai
m
How to mass close work orders based on saved search results
c
AI generated answer (using internal Slack threads):
To mass close work orders based on saved search results, you can use a combination of SuiteScript and workflows. Here's a general approach: 1. Create a Saved Search: The first step is to create a saved search that returns the work orders you want to close. Make sure the search is accurate and includes at least one filter, such as the internal ID. 2. Create a Scheduled Workflow: Next, create a scheduled workflow that triggers every 30 minutes (or any other suitable interval). Use the saved search as the criteria for this workflow. 3. Set
isclosed
to True
: In your workflow action, you need to set the
isclosed
field to true for all line items in the work order. This is similar to how you would close a sales order in NetSuite. Here's a sample SuiteScript code snippet that demonstrates how to close a work order:
Copy code
javascript
var workOrderRecord = nlapiLoadRecord('workorder', workOrderId);
var lineItemCount = workOrderRecord.getLineItemCount('item');
for (var i = 1; i <= lineItemCount; i++) {
    workOrderRecord.setLineItemValue('item', 'isclosed', i, 'T');
}
nlapiSubmitRecord(workOrderRecord);
Please replace
workOrderId
with the actual ID of the work order you want to close. Remember, workflows are great for actions within a single record but can't do much complicated work across multiple record types. If your use case is more complicated, you might need to write a more complex script. ****** Disclaimer: This response was generated by an artificial intelligence assistant based on previous conversations from multiple Slack channels, and may contain inaccuracies or mistakes. ******
Slack thread 1: here (available only if the original thread was posted in the last 90 days)
Similarity score: 0.860418081
Slack thread 2: here (available only if the original thread was posted in the last 90 days)
Similarity score: 0.827110231
Slack thread 3: here (available only if the original thread was posted in the last 90 days)
Similarity score: 0.824938893
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