How do you manage job shop complexity?
It involves manufacturing products, often complex ones, in a succession of manufacturing operations carried out on equipment specialized by technology. For example, we carry out a succession of machining, painting, and assembly operations, with detours through subcontracted operations. Each piece of equipment – a lathe, a milling machine, for example – will be used for multiple manufacturing orders. Manufacturing orders compete with each other in each work center: which one will go first? To whom are we going to dedicate the available capacity for the next few minutes, hours, or days?
This type of environment is conducive to priority conflicts.
Several, often divergent, interests are at work. The machine setter will try to minimize set-up times by grouping jobs. The workshop manager is likely to be afraid of having unoccupied operators or resources and will want to have enough work available to keep everyone busy. The customer manager will want his critical production order to take precedence over the others – especially over the orders followed by his colleagues… Oh, I forgot, surprises can also happen: there’s a quality issue, and you have to rework some parts.
These antagonistic dynamics can create bottomless pits here and there. Sometimes it seems as if a production order, a customer order, has fallen into a hole, and we’ve lost sight of it.
Let’s take a real-life example from a company we know, and visualize the flow time between two operations in the routing, through our process mining tool :
On about 1,700 production orders that moved from the second to the third operation, the average waiting time was 5 days. The third operation is carried out on a constrained resource, fully loaded, with changeover constraints, and so it makes sense to have a queue before that operation.
However, if we take a closer look at this queue, we see some strange things:
Some production orders were carried out without waiting between the two operations, but others waited for more than two months… Did you spot the bottomless pit?
Of course, when it comes to planning, we’ve taken a bit of safety – we’re currently planning a Scheduled Duration of one week and 3 days, whereas the average is 5 days – which gives us a bit of security if orders fall down the well… but as a result, the lead times we promise our customers are not satisfactory.
How to avoid this bottomless pit?
The first thing is to provide clear, shared, ongoing visibility on priorities, and on orders that get lost along the way.
There’s no doubt about it, with the buffer board below showing the queue in front of this work center: there are 36 orders in dark red that are tripping – the priority is to get them out of the hole.
But what’s also interesting is that there are 152 blue orders – which are already in this queue when they’re not needed yet… Remember that widespread fear of running out of work? There’s no risk in this case… However, there is a risk that an operator will process a blue order ahead of time while others remain in the dark red hole, especially if this avoids a changeover…
The second thing is to avoid releasing too many work orders/starting work too early.
Let’s look at this same flow and see what happens between the release of production orders and the first routing operation, in this case cutting material:
Ouch. On average, we release production orders two weeks before we start working on them, i.e. two weeks too early… and of course, some of them fall into a first well of more than 2 months.
So, to fill the bottomless pits, ensure a smooth flow and shorter lead times, you need to set shared priorities with visual shop floor management, and only release work at the right moment – it’s simple and tasteful, and also ensures that work is available for all the workstations that need to be activated.
Any resemblance to your workshop is purely coincidental… but please don’t hesitate to contact us if this is the case.
