Attached is a very early version of a model that I am creating that is intended to replicate an assembly floor where many different types of parts are made and each has different assembly, test, process, and inspection times (as seen in the PartStandards Global Table). For the sake of baby steps since I am pretty new to Process Flow, only a few part numbers are being created in the source at the moment. What I intended to happen was each item that is created at the source goes into the first queue, where the process flow assigns a TaskSequence to it that is meant to 1). claim a processor, 2). assign necessary labels, 3). move part to station, work part (using delay), then move to next queue, and 4). free up processor and rinse and repeat sequence.
The source currently assigns labels on the parts that come in based on their ItemNum (what I'm having errors with) and their Test Rig assignment (problem for down the road). What I wanted to accomplish was through the use of Assign Labels, I wanted to take the ItemNum that was assigned to each part and in turn assign it to the token of concern, then by using that ItemNum use a Global Table Lookup to find the associated AssemblyTime with that ItemNum. That way in the delay step I could simply reference the token's AssemblyTime and it would know how long the part should be taking and therefore how long the operator must wait. However, upon running the simulation, the console is swamped with Invalid Row Identifier errors for the label assignments so I must've implemented my idea incorrectly.
How can I go about accomplishing my idea? Am I misusing the label assignments or is there a different approach I could take to reach the same goal?
Also one final note, I have no way of currently telling if it happens, but I would like that if an operator does not finish their part before their shift ends, the next shift workers will pick up where they left off. Any tips on accomplishing that (or just letting me know if my current system should accomplish that) would be appreciated as well.