Reflecation paper
- Module 7- Building a Prototype Using
Off-the-Shelf Components
➢ Overview
• Often, the quickest way to realize a physical prototype is to build
the prototype using off-the shelf components.
• Most prototyping projects will require acquiring components to
make a prototype.
• The more off-the-shelf components that can be purchased and
used, the quicker the prototype can be realized.
1Dr. Munther Hermez
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❑ DECIDE WHAT TO PURCHASE
product development process steps:
1. Define the requirements
2. Produce a conceptual design
3. Produce a final design
4. Manufacture the machine or system
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❑ DECISION FOR A PROTOTYPE
Buying instead of making a component may be due to:
1. The company cannot make the component or easily acquire such
a capability and must seek a supplier
2. The supplier has a lower cost, and/or faster availability
3. The supplier’s version of the item is better for any number of
possible reasons
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changes or trade-offs may include:
• Changing power sources
• Increasing or decreasing power requirements
• Changing material selection
• Changing controller systems
• Modifying operator interface requirements
• Modification of ambient operating environment
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➢ WHAT TO PURCHASE
• The first step
is to start with a list of the derived functions for a new product with a
noun and a verb.
• The second step
is to find the relationships among the functions by arranging the
functions into a logical orderly fashion, and finding the sub functions
and its related units.
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➢ SENSOR PURCHASING
Example:
Decision-making process for case study of an oxygen-detecting
system in a newly developed chamber, includes:
1. Objective:
2. Goal:
3. Constraints/conditions:
4. Sensor system design and specifications:
5. Sensors selected:
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The sensor design result based on the functional efficiency technique.
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❑ THE NEEDED COMPONENTS
▪ EVALUATING COMPANIES AND PRODUCTS
▪ COMPONENT SELECTION
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❑ PURCHASED COMPONENTS INTEGRATION
A lot of homework needs to be done before purchasing, including:
• prototype assembly planning,
• using a CAD system for virtual simulation,
• tolerance analysis, and effective communication with the
components’ vendor.
• Functional compatibility and geometric compatibility are the keys.
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• Writing prototype specifications is critical, and it should start from
defining prototype goals as shown in Figure :
Defining prototype components specifications.
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• The prototype design goals will be matured into prototype
requirements:
- LINEAR RAILS
- MOTOR
- MOTOR DRIVER
- MOTOR PULLEYS AND BELTS
- PEN SOLENOID
- OTHER COMPONENTS
- MECHANICAL DEVELOPMENT
- VIRTUAL MODELING
- VIRTUAL ASSEMBLY
- COMPONENT FABRICATION
- PLOTTER PHYSICAL ASSEMBLY
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❑ TOLERANCE ANALYSIS
• How to conduct tolerance analysis so that parts can fit together?
• What are the commonly used mechanical fits?
• What are the definitions of these mechanical fits?
– What is a clearance fit ?
– What is an interference fit ?
– What is a transition fit ?
• How to assign tolerances to a specific fit?
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• The tolerance required will depend on the function of the part and
the particular feature being dimensioned.
• tolerance is decided by:
(a) The functional importance involved (the required mission)
(b) The economics of manufacture (avoid spending unnecessary
time and money).
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• TOLERANCE STACK ANALYSIS
• ASSEMBLY STACKS
• PROCESS CAPABILITY – process capability index Cp can be expressed as
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• Cpk measures not only the process variation with respect to
allowable specifications, but also considers the location of the
process average.
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▪ STATISTICAL TOLERANCE ANALYSIS
• The sum of the contributing tolerances is called worst case
tolerance analysis.
• The statistical tolerance analysis would not change the resulting
tolerance sum of the tolerance chain.
• sum of the tolerance, it uses the equation:
where ssum is standard deviation of the sum of the all the contributing tolerances (i¼1 n).
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EXAMPLE
A robot gripper can pick up parts within 2 ± 0.010 in.
dimensional specification.
The process standard deviation σ = 0.005 in.
Is the process ready for this robot application ? If the mean, m,
of the part dimension is 2 in. and the variation is normally
distributed,
what % of the parts will the robot be unable to pick up ?
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EXAMPLE
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EXAMPLE
Areas of probability density of the normally distributed random variable.
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EXAMPLE
From areas of the probability table as shown in Figure, the following
can be obtained:
100 - 95.44 = 4.56% of the parts will be missed.
Quality and automation go hand in hand.
The classic 3σ limits has been challenged 100% - 99.74% = 0.26 %.
i.e., 3 out of 1000 parts will fail.
Many big companies are shooting for 6σ limits, i.e.,
100 - 99.9999998 = 0.0000002 %