Process planning translates design information into the process steps
and instructions to efficiently and effectively manufacture products. As
the design process is supported by many computer-aided tools, computer-aided
process planning (CAPP) has evolved to simplify and improve process planning
and achieve more effective use of manufacturing resources.
Process planning encompasses the activities and functions to prepare
a detailed set of plans and instructions to produce a part. The planning
begins with engineering drawings, specifications, parts or material lists
and a forecast of demand. The results of the planning are:
- Routings which specify operations, operation sequences, work centers,
standards, tooling and fixtures.This routing becomes a major input to the
manufacturing resource planning system to define operations for production
activity control purposes and define required resources for capacity requirements
- Process plans which typically provide more detailed,step-by-step work
instructions including dimensions related to individual operations, machining
parameters, set-up instructions, and quality assurance checkpoints.
- Fabrication and assembly drawings to support manufacture (as opposed
to engineering drawings to define the part).
Manual process planning is based on a manufacturing engineer's experience
and knowledge of production facilities,equipment, their capabilities, processes,
and tooling. Process planning is very time-consuming and the results vary
based on the person doing the planning.
COMPUTER-AIDED PROCESS PLANNING
Manufacturers have been pursuing an evolutionary path to improve and
computerize process planning in the following five stages:
Prior to CAPP, manufacturers attempted to overcome the problems of manual
process planning by basic classification of parts into families and developing
somewhat standardized process plans for parts families (Stage I). When a
new part was introduced, the process plan for that family would be manually
retrieved, marked-up and retyped. While this improved productivity, it did
not improve the quality of the planning of processes and it did not easily
take into account the differences between parts in a family nor improvements
in production processes.
Computer-aided process planning initially evolved as a means to electronically
store a process plan once it was created, retrieve it, modify it for a new
part and print the plan (Stage II). Other capabilities of this stage are
table-driven cost and standard estimating systems.
This initial computer-aided approach evolved into what is now known as "variant"
CAPP. However, variant CAPP is based on a Group Technology (GT) coding and
classification approach to identify a larger number of part attributes or
parameters. These attributes allow the system to select a baseline process
plan for the part family and accomplish about ninety percent of the planning
work. The planner will add the remaining ten percent of the effort modifying
or fine-tuning the process plan. The baseline process plans stored in the
computer are manually entered using a super planner concept,that is, developing
standardized plans based on the accumulated experience and knowledge of
multiple planners and manufacturing engineers (Stage III).
The next stage of evolution is toward generative CAPP (Stage IV). At this
stage, process planning decision rules are built into the system. These
decision rules will operate based on a part's group technology or features
technology coding to produce a process plan that will require minimal manual
interaction and modification (e.g., entry of dimensions).
While CAPP systems are moving more and more towards being generative, a
pure generative system that can produce a complete process plan from part
classification and other design data is a goal of the future. This type
of purely generative system (in Stage V) will involve the use of artificial
intelligence type capabilities to produce process plans as well as be fully
integrated in a CIM environment. A further step in this stage is dynamic,
generative CAPP which would consider plant and machine capacities, tooling
availability, work center and equipment loads, and equipment status (e.g.,
maintenance downtime) in developing process plans.
The process plan developed with a CAPP system at Stage V would vary over
time depending on the resources and workload in the factory. For example,
if a primary work center for an operation(s) was overloaded, the generative
planning process would evaluate work to be released involving that work
center,alternate processes and the related routings. The decision rules
would result in process plans that would reduce the overloading on the primary
work center by using an alternate routing that would have the least cost
impact. Since finite scheduling systems are still in their infancy, this
additional dimension to production scheduling is still a long way off.
Dynamic, generative CAPP also implies the need for online display of the
process plan on a workorder oriented basis to insure that the appropriate
process plan was provided to the floor. Tight integration with a manufacturing
resource planning system is needed to track shop floor status and load data
and assess alternate routings vis-a-vis the schedule.Finally, this stage
of CAPP would directly feed shop floor equipment controllers or, in a less
automated environment,display assembly drawings online in conjunction with
CAPP PLANNING PROCESS
The system logic involved in establishing a variant process planning
system is relatively straight forward - it is one of matching a code with
a pre-established process plan maintained in the system. The initial challenge
is in developing the GT classification and coding structure for the part
families and in manually developing a standard baseline process plan for
each part family.
The first key to implementing a generative system is the development of
decision rules appropriate for the items to be processed. These decision
rules are specified using decision trees, computer languages involving logical
"if-then" type statements, or artificial intelligence approaches
with object-oriented programming.
The nature of the parts will affect the complexity of the decision rules
for generative planning and ultimately the degree of success in implementing
the generative CAPP system.The majority of generative CAPP systems implemented
to date have focused on process planning for fabrication of sheet metal
parts and less complex machined parts. In addition, there has been significant
recent effort with generative process planning for assembly operations,
including PCB assembly.
A second key to generative process planning is the available data related
to the part to drive the planning. Simple forms of generative planning systems
may be driven by GT codes. Group technology or features technology (FT)
type classification without a numeric code may be used to drive CAPP. This
approach would involve a user responding to a series of questions about
a part that in essence capture the same information as in a GT or FT code.
Eventually when features-oriented data is captured in a CAD system during
the design process, this data can directly drive CAPP.
CAD/CAM INTEGRATION AND CAPP FEATURES
A frequently overlooked step in the integration of CAD/CAM is the process
planning that must occur. CAD systems generate graphically oriented data
and may go so far as graphically identifying metal, etc. to be removed during
processing. In order to produce such things as NC instructions for CAM equipment,
basic decisions regarding equipment to be used,tooling and operation sequence
need to be made. This is the function of CAPP. Without some element of CAPP,
there would not be such a thing as CAD/CAM integration. Thus CAD/CAM systems
that generate tool paths and NC programs include limited CAPP capabilities
or imply a certain approach to processing.
CAD systems also provide graphically-oriented data to CAPP systems to use
to produce assembly drawings, etc. Further,this graphically-oriented data
can then be provided to manufacturing in the form of hardcopy drawings or
work instruction displays. This type of system uses work instruction displays
at factory workstations to display process plans graphically and guide employees
through assembly step by step. The assembly is shown on the screen and as
a employee steps through the assembly process with a footswitch, the components
to be inserted or assembled are shown on the CRT graphically along with
text instructions and warnings for each step.
If NC machining processes are involved, CAPP software exists which will
select tools, feeds, and speeds, and prepare NC programs.
Significant benefits can result from the implementation of CAPP. In a
detailed survey of twenty-two large and small companies using generative-type
CAPP systems, the following estimated cost savings were achieved:
- 58% reduction in process planning effort
- 10% saving in direct labor
- 4% saving in material
- 10% saving in scrap
- 12% saving in tooling
- 6% reduction in work-in-process
In addition, there are intangible benefits as follows:
- Reduced process planning and production leadtime; faster response to
- Greater process plan consistency; access to up-to-date information
in a central database
- Improved cost estimating procedures and fewer calculation errors
- More complete and detailed process plans
- Improved production scheduling and capacity utilization
- Improved ability to introduce new manufacturing technology and rapidly
update process plans to utilize the improved technology
CAPP is a highly effective technology for discrete manufacturers with
a significant number of products and process steps. Rapid strides are being
made to develop generative planning capabilities and incorporate CAPP into
a computer-integrated manufacturing architecture. The first step is the
implementation of GT or FT classification and coding. Commercially-available
software tools currently exist to support both GT and CAPP. As a result,
many companies can achieve the benefits of GT and CAPP with minimal cost
and risk. Effective use of these tools can improve a manufacturer's competitive
ABOUT THE AUTHOR
Kenneth A. Crow is President of DRM Associates,
a management consulting and education firm focusing on integrated product
development practices. He is a distinguished speaker and recognized expert
in the field of integrated product development. He has over twenty years
of experience consulting with major companies internationally in aerospace,
capital equipment, defense, high technology, medical equipment, and transportation
industries. He has provided guidance to executive management in formulating
a integrated product development program and reengineering the development
process as well as assisted product development teams applying IPD to specific
He has written papers, contributed to books, and given many presentations
and seminars for professional associations, conferences, and manufacturing
clients on integrated product development, design for manufacturability,
design to cost, product development teams, QFD, and team building. Among
many professional affiliations, he is past President and currently on the
Board of the Society of Concurrent Engineering and is a member of the Product
Development Management Association and the Engineering Management Society.
For further information, contact the author at DRM Associates, 2613 Via
Olivera, Palos Verdes, CA 90274, telephone (310) 377-5569, fax (310) 377-1315,
or email at firstname.lastname@example.org.