Finite Capacity Scheduling

Finite Capacity Scheduling Overview

Finite Capacity Scheduling (FCS) software determines operation start and finish times, and
eventually order, or requirement, start and finish times. In calculating start and finish times,
Finite Capacity Scheduling considers the limited, or finite, capacity of production resources.

To calculate start and finish times, Finite Capacity Scheduling uses time per piece or a fixed
time, along with other times such as set up and teardown, to calculate the duration of an
operation. The technique then schedules this duration onto the available time (based on shifts and
calendars) of a resource or resources (for instance a machine). When resources (machines) are
finite, other operations that are also available to be scheduled at the same time are shifted
forward, or backward, so they start or finish after the first operation scheduled. In addition to
scheduling forward or backward in time, a combination of the two approaches may be used when
employing Finite Capacity Scheduling.

The Gantt chart screen view below provides a simple example of scheduling finitely forward in
time. In the example, the three machines are available first shift Monday through Friday.
Available time is represented by gaps in the Gantt chart, while off time is represented with cross
hatching. Two orders, each with three operations, are scheduled. The three operations of Order_1
are represented in blue, while the three operations of Order_2 are represented in cyan, with part
of Operation 30 of Order_2 also appearing in red. The red color represents the portion of
Operation 30 scheduled to finish after Order_2’s due date.

First Order_1, and then Order_2, were scheduled forward. Since the machines are finite,
operations of Order_2 must wait to start until after the scheduled finish of operations of Order_1.
The “bottleneck” in this particular example is Machine_2. The time Operation 20 waits to access
this machine is what causes Order_2 to be late.

Given the volume of computations involved, computers and associated software are required to
implement Finite Capacity Scheduling approaches in “real world” environments. While Finite
Capacity Scheduling software has been commercially available for years, the advent of fast
affordable computers with graphical user interfaces and software has made Finite Capacity
Scheduling software applicable in a wide range of production environments.

Finite Capacity Scheduling software evolved to fill an obvious hole in the MRP II
(Manufacturing Resource Planning) paradigm used in most business systems. Under this
paradigm, the Master Production Schedule is input into the MRP (Materials Requirement
Planning) module, which generates shop orders for the floor to run. Due to inherent problems
with Capacity Planning, very seldom could operations departments produce shop orders in a
manner that adequately served customers.

Extensions to Finite Capacity Scheduling

As in the example above, initially Finite Capacity Scheduling software only modeled machine
constraints. Over time, the Finite Capacity Scheduling software has evolved to become more
full-featured. For example, in job shop scheduling environments, there are often more machines
than people. Sometimes multiple operations compete for the same machine, but other times there
are multiple operations available to run on multiple different machines simultaneously, but not
enough labor to staff the machines. In these environments, machine constraints and labor
constraints need to be modeled simultaneously by the Finite Capacity Scheduling software.

In other environments, the Finite Capacity Scheduling software needs to model tooling
constraints simultaneously with machine and labor constraints. For instance, in stamping or
molding operations, by adjusting tooling inserts, two or more different part numbers may be
made from the same die or mold. When one such part number is using the die or mold, another
must wait.

Finite Capacity Scheduling software has also evolved to consider materials. In its early forms,
Finite Capacity scheduling software was able to consider materials in such a way that the
ordering of materials is synchronized with the scheduling. So, if the scheduling of operations was
delayed due to capacity constraints, the corresponding requirement for material could also be
delayed. This synchronization of material and capacity supports concepts such as Lean
Production Scheduling, and results in steep reduction of inventory. More recent versions of
Finite Capacity Scheduling software include even more robust features for modeling materials.

As Finite Capacity Scheduling software has continued to evolve, and become more feature rich,
it has become known as Advanced Planning and Scheduling software (APS software).

Job Shop Scheduling

Characteristics of Job Shop Scheduling
All manufacturing environments will benefit from a good production schedule. However, to
attain maximum benefit, different environments require different approaches. One such
environment is the Job Shop. Job Shop scheduling is a special case of production scheduling. Job
shop scheduling environments are characterized by:

 typically engineer-to-order (ETO) or make-to- order

 engineering tasks that may constrain the schedule
 typically long routings, or routings of some complexity
  multiple simultaneous constraints , for example, both labor and machines
 machines that will intermix work on multiple orders (e.g. machining cells where different
orders will be loaded on different pallets)
 the need to promise a competitive completion date estimate to the customer before the
order is won
 the need to provide the customer continual status updates

Features Required for Job Shop Scheduling

Given their inherent complexity, Job Shop scheduling environments are the perfect fit for Finite
Capacity Scheduling software, or Advanced Planning and Scheduling software. Effective
Advanced Planning and Scheduling software has the robust modeling features necessary to
model the inherent flexibility in engineering departments. These departments often must be the
first steps handled by any job shop scheduling approach. For instance, engineers often will work
on more than one project simultaneously, or be preempted and moved from one task to the next.

Advanced Planning and Scheduling Software can also model the complex “one to many” or
“many to one” relationships between operations that are required in job shop scheduling. In
many situations, particularly when products are unique, modeling precedence directly through
these types of relationships make more sense than trying to define bills of material. Furthermore,
graphical output (similar to that in project management software) that shows these relationships,
as in the example below, makes the process flow much easier to follow in job shop scheduling
environments.

The ability to handle multiple simultaneous constraints can be very important in job shop
scheduling environments. For instance, sometimes multiple operations compete for the same
machine, but other times there are multiple operations available to run on multiple different
machines simultaneously, but not enough labor to staff the machines. Multiple constraints are
also necessary to model the multi pallet machining centers that are often found in job shops. One
constraint is typically used to model the spindle, and another to model the pallets upon which
work from different jobs is loaded.

Finally, in job shop scheduling environments, staff must interact with their customers over
completion dates. Often, customers are placing orders for specially engineered, or one time
orders, of product for specific applications. They need the product at a certain point in time to
satisfy their customers. Therefore, the ability to initially give prospective customers an accurate
estimated completion date is crucial. If the date you give is too far out, you end up losing the
prospect to a competitor. If the date you give is too aggressive, you won’t be able to meet it, and
you will end up with an unhappy ex-customer.

Given the importance of on time delivery, often job shop customers want continual updating
from you on when work is projected to finish. Finally, if work looks like it is going to slip, you
need to be able to know what actions to take to get completion dates back on schedule. Job shop
scheduling software that makes use of advanced planning and scheduling technology will give
you all of this capability.
Advanced Planning and Scheduling Software
Advanced Planning and Scheduling Overview
As Finite Capacity Scheduling software has evolved and become more feature rich, it has
become known as Advanced Planning and Scheduling software (APS software). Not only does
Advanced Planning and Scheduling software consider material, but it has the ability to perform
bill of material explosions which net on hand inventory and net projected inventory receipts
through purchase orders and manufacturing orders. Once inventory is netted, Advanced Planning
and Scheduling software creates purchase orders and manufacturing orders to satisfy demand
based on safety stock levels and lot sizing logic. When scheduling, Advanced Planning and
Scheduling software dynamically allocates inventory and projected inventory receipts to
production orders. If material is made constraining, the software then delays production based on
the available of inventory generated by allocated orders.

Advanced Production Scheduling software can be of significant benefit in production

environments where there are more than two levels in bills of material. Previous scheduling
techniques couldn’t delay the start of upper level items based on the schedule of components.
This limitation only allowed effective scheduling of released orders for which material is
available. Previous scheduling techniques also required manual means or MRP modules to
explode bills of material. Given the delay associated with this process, it was impossible to make
timely delivery commitments to customers.

Therefore, Advanced Planning and Scheduling software provides significant business benefits
based on its ability to explode bills of material, and delay assemblies based on the scheduled
availability of components. These benefits include the ability to:

 extend the planning and scheduling horizon for as long as there is demand to drive it.
Since demand includes sales orders and forecasts, the only practical limits are forecast
accuracy and computer processing speeds.
 quickly make accurate deliver commitments to customers.
 perform multi-plant planning and scheduling which answers questions such as “in which
plant should this production be sited?”
 plan throughout the supply chain
 deliver other benefits of a good production schedule

Advanced Planning and Scheduling Replaces MRPII

Planning
The benefits of Advanced Planning and Scheduling software allow significant changes to
MRPII’s traditional production planning / scheduling and capacity planning model. As shown in
the diagram below, the MRPII model for planning and scheduling advocates the use of different
approaches (Production Planning, Master Production Scheduling, Material Requirements
Planning, Production Activity Control) over different time horizons. Each approach has its own
version of Capacity Planning to identify and adjust for capacity imbalances. Since these capacity
planning approaches assume infinite capacity and consistent lead times, none works particularly
well.

Given its ability to explode bills of material and its ability to explicitly consider capacity, the
whole paradigm can be replaces with an effective Advanced Planning and Scheduling module.
Worst case, you might want to use two different Advanced Planning and Scheduling modules,
one for long term planning, and the other for shorter term planning and scheduling. The
Advanced Planning and Scheduling approach is outlined in the diagram below:
Capacity Planning
Capacity planning is the process of identifying necessary resources to support a production plan
or a production schedule. Depending upon the time frame involved and whether or not bills have
been exploded, more specific terms used to describe the process include resource requirements
planning, rough-cut capacity planning, or capacity requirements planning.

Historically, capacity planning is done by backward scheduling requirements (or orders)

infinitely (or without explicit regard to capacity). Starting with the due date of the order, the
length of the last operation is used to calculate the start and finish time of that operation.
Continuing to work backward in time, the start and finish of the next to last operation is
calculated, often using a delay time between operations to approximate the time the operation
would wait in queue due to constraints.

The sum of operation set up, run, and teardown times on routing operations are used to determine
the load of the operation on the resource or resources. These times can also be used to calculate
the length of the operation and, therefore, the start and finish time of the operation when it is
scheduled. Alternatively, the length of the operation can be specified in another variable.
Typically, the load time is then spread out over the length of the operation to determine the
timing over which resources are required.

When capacity planning, the availability of resources is determined using shop calendars and
shifts, labor staffing levels and quantities of machines and tooling. The availability of resources
is expressed as available hours, which can vary over time. Using reports and time series graphs,
the capacity planning load is then compared to the availability of the resources. In the example
below load is shown versus available hours:
If in a capacity planning time period, the available hours exceed load, you should reduce
available hours, reducing cost. If load exceeds available hours, you should add resources,
increasing cost. Any competent scheduling or planning software system should be able to
provide this minimum level of capacity planning. More precise production planning and capacity
planning is available through use of Advanced Planning and Scheduling software.

Good Production Schedule

A good production schedule helps manufacturing organizations lower cost, reduce inventory, and
improve customer service over all applicable time horizons. Regardless of the time frame, a good
production schedule gives visibility into when work should start and finish. This visibility
requires Finite Capacity Scheduling, and must consider all applicable constraints, including
machine, tooling, labor, and material constraints.

Good Production Schedule – Short Term

In the short term, a good production schedule should generate detailed dispatch lists for labor and
machines. These lists should show scheduled operations listed in start date order, with precise
start and finish times.

Depending upon business goals, a number of different algorithms could / should be used to
generate the dispatch lists. In general, these algorithms should look to satisfy customer delivery
requirements, while minimizing lead time, inventory, and costs. In many environments the
algorithms also have to consider sequence dependent set ups. Unproductive set up time, and
therefore cost, can be minimized by scheduling together work with like, or similar, set up
characteristics. However, if too much similar work is scheduled together, lead times will
lengthen and delivery will suffer.

Good Production Schedule – Medium Term

In the medium term, a good production schedule should synchronize material and capacity,
reducing inventory and cost. If material is not available, production should be delayed. If
material is available, its receipt should be delayed to coincide with the start of the operation
requiring it.

A good production schedule should pick machines and resources in a way that reduces lead
times, maximizes throughput, and improves delivery. The schedule should be easy to change
when the unforeseen occurs such machine break downs, labor call offs, material delays, and
quality problems. Better management of outsourcing, overtime, and maintenance should also
result from a good production schedule, as should reduced backorders and use of premium
transportation.

Good production schedules should also be usable in promising delivery dates to customers. First,
the schedule should show how a new order can fit into the existing schedule without affecting it.
Second, if the new order has priority, the schedule should be easily modifiable to show orders
negatively affected by the addition. A good production schedule will enable more accurate
delivery quoting, shorter lead times, and better on time deliver, which will lead to higher levels
of customer satisfaction, and potentially more sales.

Good Production Schedule / Plan – Long Term

In the longer term, a good production schedule, or plan, gives a manufacturing company the
ability to look far into the future, across not just one manufacturing plant, but across the network
of multiple plants and suppliers that make up a supply chain. As the time frames extend,
Advanced Planning and Scheduling software becomes a key enabler of such a good production
schedule / plan.

A good production schedule / plan should allow companies to know whether their supply chain
is capable of supporting the major strategic initiatives of the business. On the demand side, the
initiatives might include major changes in customers, markets, or product lines. On the supply
side, the initiatives might include adding or subtracting a supplier, closing or adding facilities, or
making major changes in capital equipment within facilities.