Common Shop Floor Scheduling Models and Why They Fail

The solution to better production management is rethinking the approach entirely

Mark Lilly

March 18, 2020

Shop floor scheduling is a huge headache for many manufacturers. You can’t operate without it, but operating with it presents a host of challenges. In particular, scheduling systems struggle to account for the many variables present in a typical high-mix, low-volume shop.

Each of the following common shop-floor scheduling models offers its own drawbacks, often creating one problem as it attempts to solve another. That’s why the solution to better production management isn’t implementing yet another shop floor scheduling system that doesn’t align with your reality—it’s rethinking the approach entirely.

Manual scheduling

Manual shop floor scheduling can take many forms, from a whiteboard on the wall, to an Excel spreadsheet, to a stack of papers with a work order written on each sheet. These manual approaches are cost-effective and easy to implement with little to no learning curve to get off the ground. At the end of the day, the jobs have to get done, and shop floor managers typically turn to manual scheduling because of its low barrier to entry.

However, manual shop floor scheduling also offers several inherent drawbacks. Performing the calculations manually can be time consuming and prone to errors. Staying organized with manual scheduling when you have 70+ work orders on your desk is a tall order, and you can forget about effective prioritization beyond a week at best because manual processes can only help you see what’s right in front of you.

Although DIY scheduling in a spreadsheet may provide a slight improvement in organization and data management, it’s no better than a whiteboard when it comes to giving you visibility into the work once it’s in process. Manual schedules are only as accurate as the moment they’re created, and quickly become outdated as variables on the shop floor inevitably shift.

Enterprise resource planning (ERP) software

Depending on the software, enterprise resource planning (ERP) systems can offer several advantages over manual scheduling, including automating some of the more time-consuming aspects of production planning by cutting down on manual data entry.

However, ERP software calculations don’t always reflect your reality. The software defaults to prioritizing jobs by due date, even though a job due in three weeks may actually be at greater risk of being delivered late than a job due next week because of the complexity of its operations and other factors. The resulting schedules give precedence to suboptimal jobs, leading to bottlenecks and delays in production.

ERP prediction tools may also default to assuming infinite shop floor capacity, automatically generating scheduling timelines that simply aren’t feasible once in motion. In this case, shop floor managers have to manually adjust the schedule, giving back the time they saved earlier on data entry. And, because ERP scheduling isn’t designed for extensive manual updates, these changes can be very tedious to execute, and they reintroduce the risk of human error.

Capacity-loading scheduling

Some researchers have dedicated their academic work to creating the most optimal scheduling algorithms, which may use one of several approaches to shop floor capacity and loading. Forward loading sequences each operation needed to complete the job, starting today and extending as far into the future as necessary. Backward loading starts with the day the job is due and then sequences the operations in reverse order to get the latest date you can start the work order.

Infinite capacity scheduling assumes that your shop floor will have all the time, materials, and personnel needed to complete a job on time. While this is ideal on paper, it rarely happens on the shop floor as planned. On the other side, finite capacity scheduling allows you to set constraints, then only loads the numbers of jobs that can be worked on at any given time. Unfortunately, generating schedules based solely on the hours available does not account for any changes on the shop floor, and offers an inadequate buffer to ensure that jobs are delivered on time.

Although resource-loading is great in theory, all of these approaches lack the personalized knowledge that people on your shop floor can provide based on years of hands-on experience. As a result, the estimates that these types of scheduling rely on are no match for the real-life complexities of shop floor production.

Theory of constraints (TOC)

The theory of constraints (TOC) scheduling approach was developed during the 1980s, before the rise of ERP software. TOC assumes that performance of the overall system (in this case, the shop floor) depends on the performance of the underlying constraint.

Drum-buffer-rope is a planning and scheduling system derived from TOC. The “drum” is the scarce resource that controls the output of the shop floor. “Buffer” refers to the extra time built into the process, and “rope” refers to synchronizing all the discrete processes so no part of production moves too fast or too slow.

TOC and the drum-buffer-rope approach to scheduling assume that there is only one constraint, and that all other requirements can be met. In manufacturing, this constraint is almost always the due date, which offers an incomplete picture of what’s actually happening on the shop floor. There may be multiple competing constraints the shop floor must be accounted for, and the due date may not be the most accurate way to prioritize work orders.

A better way forward

The solution to delayed work orders isn’t another scheduling system. Clearly, manufacturers have plenty of those to choose from already, and they all offer significant obstacles to on-time delivery. Instead, a new approach to managing production is needed, starting with a focus on better flow.

By speeding up the flow of information and materials throughout the shop, manufacturers can start to realize some of the false promises they’ve been fed for decades by traditional shop floor scheduling models.

Promoting better flow starts by following these three principles:
Anticipate and account for variability on the shop floor (stuff happens; can your scheduling solutions adjust once it does?).
Control your work in process (WIP) (flooding WIP confuses your true priorities and increases the chance that the “wrong” job will be selected to work on next).
Prioritize what must be done next to deliver on time (as opposed to prioritizing solely based on due date).

Without visibility into in-process work orders, your shop floor is always executing against an outdated schedule and can’t account for any of the above principles. Instead of fixating on perfecting the schedule, manufacturers need to focus on increasing the flow of actionable information to those who need it to gain this critical visibility. Without it, making decisions on what to prioritize next will continue to be an exercise in “best-laid plans” vs. executing based on the moment-to-moment reality of your shop floor.

To learn how to drastically improve the flow of information and materials to increase the speed of execution in your shop, request a consultation with the production planning and execution experts at LillyWorks.

About The Author

Mark Lilly’s picture

Mark Lilly

As president and CEO of LillyWorks, Mark Lilly and his world-class team have been developing technology solutions that help manufacturers deliver better since 1960.