A 



B 

Benchmarking
Performance 
See
manufacturing efficiency studies 


C 

Centerlining 
Process
for determining optimal machine operating points usually done using
Design Of Experiments (DOE) procedures. 
Contingent
Labor 
Personnel
working for temporaryhelp or contract staffing agencies assigned
to work on other companies projects for as long as the project lasts. 


D 

Design
of Experiments (DOE) 
Method
for determining which and how many experiments to be run to reach
conclusions on the importance and dependency of parameters. Parameters
are variables: constituents, tolerances, setpoints (e.g. food ingredients,
machine operating set points, and product allowable dimensional variations) 
Discrete
Event Modeling 
Operations,
either manufacturing processes (e.g. work piece flow, "making"
equipment or "converting" equipment operation flows) or
service related (e.g. airport hub flow, banking queuing, telecommunications
hub and signal processing) can be modeled as a numerical simulation
based on the probabilities of occurrence of individual events. The
simulation steps through one event at a time, using a Monte Carlo
random number generation approach and the probabilistic distribution
for determining the next event. To improve the accuracy of the simulation,
numerous simulation runs or "trials" must be made and combined
into new probabilistic distributions for the events of the process.
See queuing theory modeling. 


E 

Efficiency
Studies 
See
manufacturing efficiency studies. Application of the same techniques
to any type of service process (e.g. accounting operations, management
decision making, IS department support operations) 
Energy
Audits 
Process
of evaluating and systematically detailing energy consumption of equipment
in buildings and manufacturing processes. The next step after the
audit is to develop a detailed plan for reducing energy consumption
and to determine the ROI (Return On Investment) from the costsavings
analysis. 


F 

FD 
Finite
difference is another numerical modeling method similar in principle
to FEA but using different and simpler numerical solution methods.
It is particularly well suited to 2D flow network analysis and 2D
heat transfer analysis. 
FE
or FEA 
Finite
element analysis is a numerical modeling method originally developed
by civil engineers to analyze truss structures and now applied to
analysis of stress, heat transfer, fluid flow, vibrations, and electromagnetic
fields. It is used for the analysis of complex shapes and systems
that would otherwise be difficult to perform by hand calculations.
FEA methods allow more precise analysis results enabling the designer
to eliminate safety factors previously used to protect against unknown
and unaccounted for stresses and other design parameters not easily
calculated by hand. 
Forensics
Engineering 
Engineering
analysis undertaken to determine the cause of system or component
failure. Failures can be caused by material defects, operating conditions,
lack of analysis to set operating limits, manufacturing reliability
problems, errors in analysis verifying design features, inadequate
safety features among others. 


G 



H 

Heat
Transfer Analysis 
Engineering
analysis of heat in which all sources, all sinks and the medium(s)
through which the energy is carried are identified. The rate of heat
transfer, either into or out of the component, as well as the capacity
of the component to hold heat is determined. And finally, the effects
on material properties and stresses from heat buildup or cooldown
are determined. 
I 



J 



K 



L 



M 

Management
Consultants (Management Advisory Services) 
Advice
CEO to CEO on a wide array of topics usually on a retention basis.
Possible topics: accounting system choices, IT maintenance options,
engineering software decisions, HR (Human Resources) recruiting methods,
recruiting choices, retention programs and benefits, manufacturing
cost reductions and efficiency increases, manufacturing location selection,
corporate headquarters selection, marketing studies, advertising agency
selection and performance criteria, research into the selection of
any number of outside service providers, among many others. The idea
is to retain outside advisers to provide unbiased advice and opinions
on any topic to managers do not have time to do research themselves
in an effort to understand the current market. Management advisors
often act to counter salespersons' pitches since they have no vested
interest in the product being sold. 
Manufacturing
Efficiency Studies 
Process
of: 1. determining the optimal performance of a process 2. comparing
a current manufacturing operation to the optimal performance and 3.
determining how to change the current process to become more like
the predicted optimal performance. 
MCAD 
Solid
modeling CAD (Computer Aided Design) software 
Monte
Carlo 
Method
employing random numbers, called seeds, in which all the probable
seeds are assigned a likelihood of occurrence. For each time step
only one seed is generated which represents the event. For an event
having a 50% probability of occurring, 50 out of 100 unique seeds
are possible to represent that event. 


N 



O 

Outsourcing 
Practice
of using human resources working for other companies to perform company
required tasks. 


P 



Q 

Queuing
Theory Modeling 
Queuing
theory is different from discrete event modeling in that it is a system
of formulas representing a system that takes inputs, such as manufacturing
product arrival rates and service time, and delivers results including
average time in system and average utilization of resources. Systems
modeled by queuing theory must be represented by formulas and therefore
cannot be complex representations. Queuing theory cannot handle real
statistical distributions of events and instead uses "Erlang"
distributions that are calculated only once and tend to yield average
results as opposed to discrete event simulations in which multiple
runs known as "trials" must be calculated from representative
statistical distributions in order to arrive at results that could
actually occur over time. Queuing theory results always fall somewhere
within the discrete event trial confidence limits results. 


R 

Reliability
Engineering 
Methodology
for designing equipment systems in which known and assumed component
failure rates are considered in an effort to design the system with
higher uptime rates than would be possible otherwise. 
Reverse
Engineering 
Process
of examining a process, product or machine and creating the original
detail drawings and operational parameters. The examination process
includes assessing the materials of construction, measuring all parts,
determining tolerances from the manufacturing processes used, and
creating the Bill of Material list including OfftheShelf parts specifications.
Reverse engineering is typically done to understand competitors products
and to specify products developed and manufactured by suppliers and
"prototypists" not furnishing detailed plans. 
Root
Cause Analysis 
Systematic
approach to finding all levels of system interactions in an effort
to determine the true cause of system failure. 


S 

Six
Sigma 
Quality
program first developed by Motorola and expanded by GE to improve
the statisticallybased quality improvement efforts in manufacturing.
Named 6sigma because the goal in reducing part defects is to reduce
meaningful deviations to nearly zero. GE and many other companies
now apply 6sigma techniques to every aspect of their business as
a rigorous continuous improvement regimen to redesign operations into
processes of doing work having little or no potential for error. Is
in direct conflict with programs to develop and improve the creativity
and innovative nature of people and their new product ideas. 


T 

TRIZ
(sometimes called TRIS) 
(Theory
of Inventive Problem Solving). A methodology and database first created
by G. Altshuller to enhance the flow of ideas or innovation while
solving engineering design problems. The database is comprised of
sets of associations common among nearly all patentable ideas and
is referenced while the designer breaks the design problem into fundamental
engineering areas such as materials and energy forms (e.g. electricity
and chemical composition). 


U 



V 

Value
Engineering 
Subset
of manufacturing engineering in which statistic methods, like six
sigma, are employed to determine the best value choice among all possible
decisions. 


W 



X 



Y 



Z 


