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This last notion of creating an acceptable schedule is one of the key features of a good APS engine that can lead to significant results in manufacturing. Even with all the capabilities of a powerful APS engine to create a finite schedule based on the factory that it models, the ability to change the model and simulate the results of a change are vital. If we are looking for schedules that we can expect to be followed, the process to get buy-in must be very receptive to input. What we have seen re­peatedly is that although APS will generate a high-qual­ity finite schedule, unique circumstances, product mix or data error can cause a schedule to be erroneous— maybe not entirely wrong, but not good enough to be credible. The most successful APS implementations must bring the APS scheduling process to the floor. Es­pecially in the initial phase of APS use, a review of the schedule is an essential part of getting manufacturing to accept that a schedule is feasible.

Equally important as generating a doable schedule is creating trust in the schedule to the point that people will accept accountability for the performance of that schedule. To get manufacturing to accept performance accountability requires reengineering what is typically called the "daily production meeting."

Somebody or some process always decides what work is placed on a resource. Elaborate dispatch rules, hot-lists, visual signals or operator whim makes the selec­tion from jobs queued at a machine—but a selection is always made. The daily production meeting generally attempts to guide and coordinate what jobs should be pulled to the front of the queue. Key customers and his­toric bottlenecks are generally some of the top criteria used to prioritize the special expediting. In fact, often, "the schedule" is not discussed during many daily pro­duction meetings—frequently the "customer backlog" or a "revenue report" are the dispatching tools.

The following "production meeting" process is most successful with APS:


1.      Evaluate the doability of the schedule—Customer
priorities, due dates and resource considerations have
already been optimized, performance to need be­
comes the primary consideration. APS tools gener­
ally highlight jobs that are late due to resource
constraints. Visual Gantt charts, colors and drill-
down capabilities help determine the root cause of
the lateness.

2.      Review options to improve due-date performance—
APS is a decision support tool that must allow users
to suggest "what if scenarios and run a quick simula­
tion of the schedule under new conditions (overtime,
outsourcing, alternate routing, setup-time-dependant
sequencing, various scheduling and dispatching rules,
etc.). Compare the results of each change and select or
reject each alternate scenario.

3.      Fix any detailed data—Data errors that affect the
doability of a schedule surface during the schedule
review. Data cleanup is often one of the most ne­
glected processes in operations. By focusing on re­
sources that are current constraints, the data most
important to achieving immediate results is cor­

4.      Commit to the schedule and just "do-it"—The de­
tailed level of an APS finite schedule provides spe­
cific optimal job sequence and provides management
at all levels the ability to monitor performance to

The above steps can be expressed simply as: create a doable schedule, then do-it. A process too simple to be revolutionary—yet desperately needed by most manu­facturers.


The first two steps in the above "production meeting process" are generally where individuals with CIRM, CPIM, or CFPIM credentials focus the majority of their attention. It is critical that an APS system be powerful enough to exactly model your manufacturing process, and flexible and fast enough to easily simulate how you can respond to bottlenecks and late deliveries. The key in se­lecting the right software for your use is that it can act as a decision-support tool to help operations improve de­liveries. Finite schedulers should not become tools that identify limited capacities as an excuse for not making the business plan. APS must be a tool to optimize the plan against resources and provide valid dates that can be depended on. I will not focus on the many features and techniques available in various APS software; how­ever, I will say that close is not good enough in modeling your shop to get buy-in on a schedule.

The third step is an exciting "bonus" part of this pro­cess. Reasons companies struggle with implementing ERP systems or comprehensive manufacturing strate­gies are the requirements for high degrees of data accu­racy and process integrity, and cross-functional involvement and process reengineering required to implement "the project." The review necessary to get the buy-in of manufacturing will require a validity check of the APS plan. Managers who are trying to improve due-date performance must challenge data that is too con­servative. Operators being held accountable for their attainment of the schedule challenge data that is too aggressive. The data that is influencing the load on a constraint is auditable and APS tools allow correction to be simulated and a valid schedule to be prepared. The efforts of your key operating people are focused at cor­recting the data relevant to making current requirements happen. The critical data affecting critical bottlenecks is reviewed and fixed during the production meeting with a new re-optimized schedule generated and the detailed impact of those corrections immediately un­derstood. The continuous improvement of the most important data has a cumulative effect on improving enterprise information for work centers or items that present bottlenecks. Unlike other data cleanup projects, the effort is focused on data that matters to the busi­ness, data that helps managers alleviate late orders, and data that helps operators fix unreasonable standards.

To Be Continued

For balance of this article, click on the below link:

Lean Manufacturing Articles and click on Series 14

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