Three papers on five-axis milling propose a tool path smoothing algorithm, a cutting force model for ball-end milling, and a simulation kernel for calculating removal volume per tooth.
What does SA stand for?
SA stands for Smoothing Algorithm
This definition appears frequently and is found in the following Acronym Finder categories:
- Science, medicine, engineering, etc.
See other definitions of SA
We have 222 other meanings of SA in our Acronym Attic
- Site Assessment and Remediation
- Situation Assessment
- Situation(al) Awareness
- Situational Analysis
- Situational Awareness
- Sleep Apnea
- Slowly Adapting Fiber (In Skin)
- Small Arms
- Smart Alec
- Smart Ass
- Sneak Attack (gaming)
- Sniper Assist (gaming, Starcraft)
- Social Accountability
- Social Actions
- Social Anxiety
- Socialist Appeal
- Sociedad Anónima (Spanish company designation)
- Sociedade Anônima (Corporation; Brazil)
- Sociedade Anónima (Portuguese company designation)
- Societate Pe Actiuni (Romanian: stock company)
Samples in periodicals archive:
Smoothing algorithms convert small line segments back into complex curves that can be processed faster by the CNC and reduce machine shock.
Missing data It is easy to see that the backward recursion of the smoothing algorithm does not depend on the observations while the forward recursion depends on the observations.
It guides viewers through the new analyses, including time-temperature superposition, and peak and valley determination, and also examines the value of data smoothing algorithms.
Introductory discussion addresses scheduling and resource management and the algorithmic approach, which is followed by coverage of modeling servers and streams, disk scheduling in serving single CBR stream and multiple CBR and VBR streams, allocation strategies for single disks and using a multi-zone disk, storage on multiple disks including striping and random redundant storage, data transmission methods including bit-rate smoothing algorithms, and near video-on-demand strategies.
The article then describes a state-space representation, demonstrates how any model written in this form can be estimated using a Kalman filter, and explains how any unobservable variables of the model can be recovered from the data using the smoothing algorithm built into the Kalman filter.