Optimization Please

Oil pump manufacturer experienced a myriad of issues when one of their main lines went out of operation unexpectedlyPain Points Summary:Manufacturer failed to schedule preventative maintenance on their lines, resulting in an unforeseen issue knocking out a line for two weeksThe operation leader and team of schedulers spent two full days working to reallocate orders to other lines in the plantStaff was unable to see the impacted orders and customers tied to the issueOil pumps set to be produced on other lines experienced delays due to a temporary halt in the operationManufacturer expedited the parts needed for the repairs – raising the cost of the line failureEmergency shifts and overtime was utilized to extend the run times of other lines to make up for the line outageDelays in orders being produced and in-hands dates were pushed out 1 to nearly 2 months in some casesManufacturer was unable to accept new business opportunities during the time of the line issueMany customers cancelled orders when the new in-hands date to account for the delay was communicated to them by the account teamOptimization Summary:Easily plan and schedule their production around required or scheduled maintenance windowsComplete line balancing optimizations to shift production to another line or bunch of lines to account for maintenance windowsImpacted customers, orders, and shifts in delivery dates are easily visible in a color-coded charts, graphs, and tablesIn this case, accounting for an unforeseen issue, the ability to replan and reschedule given the unfortunate circumstance would take minutes, not daysManufacturer would save on expedited shipping costs to obtain necessary partsNo emergency shifts or overtime would be needed to account for or make up for the line outageUpdated delivery dates can be communicated to the customers in a timely manner – saving the order or reprioritizing around the delayManufacturer can keep accepting new business opportunities

This episode focuses on an automotive OEM’s paint shop operation.This automotive company has operations around the world but the paint shop operation I will be focusing on has ties to their vehicles produced in the eastern parts of the United States and western parts of Europe.The simplified problem statement from the customer was this:Help us to paint our vehicles in the most efficient manner while considering time and material constraints.The complex problem statement and scope from the customer:We need to properly sequence our paint shop operation which is tasked with painting upwards of 10,000 vehicles a week, some two-tone, while considering our utilization of paint, solvents, water, labor resources, and of course the dealer delivery dates where expedited shipping should be limited to reduce overall costs to the company.

Episode Summary: Metal fabrication provider wanted to make sure their top customer, based on revenue, was always given priority when sales input an order from themPain Points Summary:Sales dropped orders into the ERP and CRM systems at all hours of the day – typically after the 1st hour of shift one beginningSales would promise a delivery date without consulting the plannerPlanning team would scramble to shift orders around based on the updates from salesPlanning team would lose 3 days every time the customer was given priorityOther customers would experience delays on delivery, without being provided with noticeCompany lost 30% of its customers in 2 years due to the issues with customer prioritizationOptimization Summary:Sales orders would automatically sync with the current schedule for the given shiftAccurate delivery dates were provided to the top customer + impacted customers because of the prioritizationPlanning team would take less than 1 hour to review impacts to the plans and schedulesSales team would get ahead of delays or shifts in originally promised delivery datesCompany could increase conversations with their customers and sell moreCompany uncovered capacity to deliver orders ahead of schedule