Finite capacity scheduling evolves for the job shop

How advanced planning and scheduling works with reality, not assumptions

You are a high-mix, low-volume fabricator. The nature of your business dictates that at least some of your production is made to customer order. When a customer places an order, how do you and your customer service staff make delivery promises?

When prospective customers call your customer service department and ask for a quote, they typically want to know how much a job will cost and when they will get it. You may think that the price quote is most important. While price certainly influences your margins, the delivery date you supply can have a more significant impact on how your organization runs and, therefore, on your overall profitability.

How are you quoting delivery dates now? You’re probably basing them on an average lead time. By their very nature, average lead times are always wrong. This average probably wasn’t calculated carefully and almost certainly is not being updated continually. It may have been based on customer demands that have changed significantly. Also, the average lead time probably doesn’t consider the almost daily changes in shop floor capacity and performance.

Given the inaccuracies in your lead times, your customer service staff are probably using them as little more than a reference. Worse yet, in an eagerness to please customers and to hit company sales goals, they’re probably promising dates that are overly aggressive, and they may not be considering prior commitments. What choice does customer service have? If you aren’t the sole source for the part, and your company quotes a delivery date too far in the future, the customer will go to a competitor.

While lost sales opportunities are bad, saddling your business with overly aggressive promise dates is even worse. Overly aggressive promise dates put your operation in an immediate past-due state. Not only are you at risk of missing the orders just promised, but other orders in your shop could be pushed beyond their promise dates and, therefore, ship late. It’s a competition for available capacity. Some of those other (now late) orders might belong to the very customer that sent you the hot job in the first place. Talk about a Catch-22. “Yes, I know you did me a favor last week taking that order on short lead time,” the customer says, “but how could you be late on these other orders? You’ve had them for six months!”

Embarrassment aside, a manufacturer with many past-due orders is an inefficient manufacturer with an unnecessarily high cost structure. When you are behind and scrambling to catch up, you will use overtime injudiciously, break down setups prematurely, waste time expediting, run the “wrong stuff,” and build unneeded inventory.

How can you promise delivery dates better and therefore run your business more profitably? Start by acknowledging what we all know to be true: Your lead times are influenced by both your shop’s capacity and what other orders are already scheduled on that capacity. If you had a way to explicitly consider your capacity and the current load on that capacity, your promise dates would be much more accurate. Fortunately, such a way exists. It’s called finite capacity scheduling.

Considering Capacity and Constraints

At its most simple level, finite capacity scheduling software blocks out operation time (including setup, run, and teardown times) on machines. It calculates operation start and stop times and gives the shop floor a detailed, achievable dispatch list.

Finite capacity scheduling software has evolved into what often is called advanced planning and scheduling (APS) software. APS considers the totality of your capacity—not just machine capacity constraints but additional concurrent constraints such as tooling, labor, space in ovens, and material availability.

The constraints it manages allow you to build a very detailed model of your capacity and the load on that capacity. As you schedule existing operations of orders, relevant capacity is “reserved.” Operations are pushed forward or backward in time based on the priority assigned by the software’s algorithms. Highly accurate operation and order start and finish times are calculated. It’s also possible to include user-defined rules specific to the process and equipment characteristics of your shop.

Orders and operations for the work to be promised must be in the software for it to schedule. In some environments users can manually enter the needed data or transfer it from existing systems. However, it may be easiest for you to explode a bill of material (BOM) for a planned purchase order, netting on-hand component inventory and supply orders for needed components.

Combination Scheduling

APS has other tools to help you keep your delivery promises. This includes forward/backward combination scheduling. Forward scheduling starts from today and schedules operations out in time. However, it can result in orders scheduled significantly earlier than needed.

Backward scheduling starts at the order’s due date and schedules operations backward toward today. However, it can result in operations scheduled before today, which of course is not realistic.

Forward/backward combination scheduling gives you the best of both worlds. Operations won’t start before today, but likewise won’t start significantly before their due date. Combination scheduling typically leaves gaps in the schedule. These gaps represent unused capacity that you can use for order promising.

Combination scheduling is similar to drum-buffer-rope scheduling used in the theory of constraints, where your constraint or bottleneck process governs your throughput, but with one major difference: You aren’t making assumptions about the bottleneck on any given day. This can be especially beneficial in a job shop, where bottlenecks change with the mix of work.

Fit Scheduling

Another APS software tool is fit scheduling for a new order and promised delivery date, used when there are no available gaps in the schedule. Fit scheduling forces an order and promised delivery date into the schedule and pushes existing orders back in time. You’d use this feature when hot orders need to be delivered sooner than existing orders.

What If?

The customer may not accept every delivery date you propose. In this case, APS can run and save what-if scenarios. You also need to compare the what-ifs on your business’s key performance metrics. For instance, if you try a scenario where you force a hot order into the system, you will want to know which existing orders are affected and by how much.

Outside of regular scheduling, you also can simulate capacity changes (what if I added this machine or that person to this operation?) and sales/demand forecasts. If you want to simulate capacity changes and experiment with varying forecasts, you’ll likely need a software architecture that supports multiple users engaged in more than one type of task.

Get Real on Delivery

Stop fooling yourself by promising unrealistic delivery dates. Improve both on-time delivery and shop floor cost performance by considering the true capacity limitations of your operation. Finite capacity scheduling is one tool that can help you get there. Match the tool with a competent scheduler, and success is yours to enjoy despite being tasked with managing one of the most complex production systems that exist—a custom fabrication job shop.

Charles Murgiano is founder and principal of Waterloo Manufacturing Software,781-237-2678.

Creating a World-class, On-time Delivery Culture

Shahrukh Irani, PhD, president of Sugar Land, Texas-based Lean and Flexible LLC, has helped job shops implement continuous improvement for years. He’s also a proponent of finite capacity scheduling. Regardless of the exact method, scheduling needs to be based on actual available capacity and real constraints.

Say you measure how quickly a job flows from order entry to the shipping dock. Then you measure the job again and get a completely different result. What happened? The variabilities of the job shop—hot jobs, fork trucks driving back and forth, and capacity constraints—have struck again.

“For custom fabricators to achieve world-class, on-time-delivery performance, their priority should be to implement practical solutions to age-old problems,” Irani said. “First, identify product families in the product mix. Second, design a flexible facility layout that fits the material flow inherent to their product mix. Third, issue a feasible daily production schedule that was generated after consideration of all known resource constraints.”

The first step involves grouping products into families. Irani uses a product-process matrix, with parts on the vertical axis and processes on the horizontal axis. Charting the thousands of jobs that a fabricator processes may be impractical at first, so fabricators can start with selected products that represent the shop’s core type of work.

The idea is to find parts that share similar processes and other characteristics, including demand consistency: jobs that run consistently, repeat orders, all the way down to unique orders and one-offs (Irani calls these runners, repeaters, and strangers, respectively). Products in a family need not come from the same customer, but they need to share at least some manufacturing attributes, preferably a group of machines co-located in a flexible fabrication cell.

This forms the basis of a flexible shop floor layout that focuses on flow, not “process villages.” A shop may not have physically co-located work cells, considering the mix of products that flow through a custom fabricator. Exceptions will arise, but as Irani explained, those exceptions should be scrutinized and have practical solutions to address each of them.

Irani conceded that, when it comes to layout ideas, facility limitations (like plumbing, ventilation, and walls), financial considerations, and equipment availability may throw up roadblocks. But the important thing is for everyone to think about flow, put ideas on the table, and keep the focus not on how many parts per hour a certain machine produces, but instead on how quickly a job moves through the company. Irani described this as developing a “move our money mindset.” Idle work-in-process is like cash that can’t be used. Everyone should keep an eye out for idle work and “move the money” to the finish line. A company can’t make money until the order ships.

Explaining further, Irani recalled visiting an aerospace fabricator. “I observed that orders were piling up at a pressure test tank, but nobody was at that station. In fact, the workstation remained idle all day. When I arrived the next morning, and I noticed the number of orders in queue had increased, I asked the operations manager, ‘Where’s the operator?’ He replied, ‘He called in sick.’ Not satisfied by that reply, just before lunch, I went back on the floor, but this time discovered that one employee, who had been doing bench work all along, was now connecting the pneumatic and water lines to test the first order in the pressure test tank. Clearly, that person was cross trained, but he had not seen the need to stop what he was doing and start doing benchwork until he was told to do so.

“For on-time delivery performance to improve, the general manager and operations manager will need to work together to ingrain a

Scheduling is a critical piece of the delivery puzzle. But even the most sophisticated schedulers in the world can’t create perfect flow and world-class delivery performance on their own. First, people need to care.