Experienced shop floor supervisors and production managers can often find themselves at odds with the production planning function in a manufacturing business. Tensions emerge between the organisational desire to trust the principles of Materials Requirements Planning (MRP), which is often the core module for determining works orders to be manufactured, and the hard-won experience of managing materials through workstations.
The theory sounds fine; assign a lead-time to each component part, enter the due date for the finished product into the system, along with an order quantity, and the planning system will back-calculate the date by which the material is released to the factory.
Factory supervisors would argue that the assumption that lead-times remain constant is fatally flawed. The planners might reply that if the production schedules were adhered to, everything would work as intended.
Taking a scientific approach to production planning, by constructing simulations of manufacturing systems, we can observe that any variation in actual lead-times can wreak havoc on the performance of the overall system. A system where material is pushed into the factory as a consequence of a due dat and fixed assumptions of process lead-times is extremely sensitive to line stoppages, operator absence and material shortages.
Simulation illustrates that there is a direct relationship between lead-time and the quantity of Work-in-Progress. If the WIP increases, so does the lead-time. If you keep pushing material into the system because that is what the MRP software says, the WIP will increase, and therefore so will the lead-time. Orders that become overdue just get added to the list of works orders, and the cycle continues until other measures such as overtime are taken. Production planning can become a nightmare.
The issue here is that MRP does not take into account the WIP levels for a given system. It assumes that the constant lead-times shall manage a constant level of WIP.
Staff on the shop floor realise this, though it isn’t always that intuitive how to solve the problem.
Kanban is often hailed as the solution, as part of a Lean implementation. WIP is explicitly controlled at each workstation in a Kanban line. The material cannot be released for processing until a Kanban card becomes available – it is pulled through the system rather than pushed as with MRP. As soon as Kanban is installed, a dramatic reduction in WIP is observed immediately, which is good news until a stoppage occurs. Lean systems use this “threat” to have everyone focus their attention on the stoppage to resolve the problem, with the aim of eradicating the stoppage permanently.
However, this still doesn’t always rest easy with the shop floor supervisor, who only truly settles when the bottleneck process is kept running.
In a manufacturing system, the bottleneck governs the output of the system as a whole, and should therefore be utilised as much as possible. The way to do this is to ensure that there is a suitably sized buffer of jobs in front of the bottleneck to keep it going. Starving the bottleneck is starving the factory of capacity.
The granular control of WIP at every workstation can therefore be too restrictive for some production lines, especially where setup times are lengthier or there are just more stoppages in general.
Maintaining a constant level of WIP for the system as a whole, rather than between individual workstations, is the approach referred to as CONWIP. Since CONWIP does not control the individual transit of material between workstations, that material is permitted to flow freely within the factory.
The emergent effect is that it queues at the entry to the bottleneck, which is exactly what the production manager wants. This keeps utilisation of the slowest process as high as possible, while still restricting the flow of new material into the system, which would adversely affect on-time delivery of finished goods.
WIP control is a fundamental concept for the management of a production facility. IIoT can help enable WIP management by monitoring the utilisation of the current system bottleneck, and controlling the release of new material into the system in response to natural variations in process cycle time. This is particularly important for manufacturing systems that need to deliver mass-customisation for customers.