Glossary
SPC and InfinityQS Proficient
Prepared by Connie Dello Buono

Access Rights – Most networks are set up with ‘access rights’ where an administrator has set up each person who can log on, with the right to access certain files and folders.
Assignable Cause Codes (ACC) – list of items used to identify the potential root cause(s) of a problem within a process.
Alarms – Notifications of the occurrence of an event. The moment an alarm or defect occurs, ProFicient sends automated alerts, helping users better understand and control manufacturing operations. ProFicient can convey alarms through email notifications and by passing information outside of InfinityQS such that flashing lights can be illuminated on the shop floor, an audible alarm can be sounded, or customizable windows can pop up on any workstation.
• Statistical Alarms – InfinityQS can trigger alarms based on any combination of Western Electric rules. Non-statistical alarms can also be triggered in such situations as when a subgroup has been disabled, when a data value falls out of specification, or when a subgroup has been edited. Additionally, default alarm rules can be edited or modified to suit your specific needs. You can even create your own custom alarm rules.
• Data Collection Alerts and Alarms – Your company may require data to be collected regularly based on time-specific intervals. ProFicient allows you to easily specify when, where and how data collection must occur. If an operator must enter data every hour, ProFicient reminds them with large pop-up notifications. Acceptable time windows can be specified, allowing flexibility for when data must be entered. If data is not collected, ProFicient saves a detailed notification to the database, sends email(s) alerts, and optionally locks out the operator from further data collection. Additionally, ProFicient can require users to enter an Assignable Cause and a Corrective Action for why data was not collected.
• Process Event Handling – This feature automatically logs downtime and events to the database while optionally requiring Assignable Causes and Corrective Actions to be entered. Detailed event information and related control chart images are automatically emailed to engineering and managerial staff via a company’s existing email application.
• Fully Automated Notification Management – Instead of manually monitoring and reacting to events, InfinityQS products allow fully automated notification management. Remote Alarm Monitor Service (RAMS) and Remote Event Monitor Service (REMS) automate shop floor data monitoring with real-time event-logging and communications with external systems.
• Process Alarms – Visual indicators on the Plant Floor Interface of a statistical rule violation in the process or of data out of definition specification limits.
• Automated Alerts – Condition-based communications to staff members over email/SMS.

Descriptors – user defined parameters to categorize quality data
Descriptor Name
Air Type Non-Viable Air
Air Type Micro Air
Business Unit Knee
Robo Drills R-DRILL4

ProFicient saves the selected descriptor inside the Project Initialization file in the workstation. When the project is reopened, ProFicient automatically loads the previously selected descriptor.
If you are using Command Line parameters to preselect descriptors (for example, MyProject.IPJ /Part=Blue Part /Lot=BP225), ProFicient will also update the Project Initialization file with these command line descriptors.

Audit trail – Can be displayed by going to report setup > show audit table box (yellow color), creates an audit trail entry.
Box & Whisker Plot – A graphical way to illustrate multiple distributions using a shared scale. Some say that a Box and Whisker plot is like a top view of a histogram. Used primarily for comparative analysis among several distributions. Used to describe the shape of the distribution. Used to provide an idea about the center and spread of a data set.
Buffer file – Serial To File. With Serial To File you can configure any Gage Server device to output to a text file. This text file (or buffer file) can be linked to any descriptors or tests within a data entry configuration. You can simply set your solids analyzer to output to a text file as soon as the sample is finished with its test and the value will sit and wait for the technician to perform a routine check – hence “buffer” file.
CAC – Corrective Action Codes; list of items used to identify the action(s) taken to correct a problem with a process.
Calculated Control Limits – Control limits automatically calculated by the software each time a new subgroup is added to the dataset represented on the chart.
Camstar MES – Manufacturing execution System
Capability Report – A spreadsheet-like window that allows each row to be configured with a different Part, Process and Test characteristic combination and provides all process potential indices, process performance indices, mean, range, standard deviation and other descriptive statistics.
c-Chart – An attribute chart used to plot the number of defects per subgroup. Chart requires the sample size to remain constant.
Chi-square statistic – used to measure the agreement between categorical data and a multinomial model that predicts the relative frequency of outcomes in each possible category.
How Well Does Your Mental Model Fit with Reality?
The chi-squared statistic summarizes the discrepancies between the expected number of times each outcome occurs (assuming that the model is true) and the observed number of times each outcome occurs, by summing the squares of the discrepancies, normalized by the expected numbers, over all the categories:
chi-squared = (observed1 – expected1)2/expected1 + (observed2 – expected2)2/expected2 + . . . + (observedk – expectedk)2/expectedk.
As the sample size n increases, if the model is correct, the sampling distribution of the chi-squared statistic is approximated increasingly well by the chi-squared curve with (#categories – 1) = k – 1
degrees of freedom (d.f.), in the sense that the chance that the chi-squared statistic is in any given range grows closer and closer to the area under the Chi-Squared curve over the same range. All but one have the freedom to change, but once they are fixed the remaining one is fixed too.
Chi Square tests use discrete, count data, arranged in a matrix of rows and columns, to look for statistical differences among populations.
Citrix – Hosting app thru citrix, means non of the client terminals will have no SW install, but has the citrix receiver. It launches app using virtual hosting environment.
CNC machines – Computer Numerical Control machines
Coded – This processing is required when combining characteristics on the same chart that are of different units of measure, different expected levels of variation or different expected fallout rates.
Command Line Line Parameters Incorporate Reselect Functionality – When you reselect a descriptor during Add Subgroup or toolbar function (for example,
Control – The state of stability, normal variation and predictability. Process of regulating and guiding operations and processes using quantitative data.
Control chart – Monitors variance in a process over time and alerts the business to unexpected variance which may cause defects.
Control chart type group options (part,process,test):
• Plots and analyzes multiple data streams on one chart.
• Each data stream is processed individually.
• They are grouped together and the minimum and maximum points from each group are plotted.
• Control chart type using Time Threshold to force grouping of data within specified time periods. Control chart type processing options:
• Traditional: No normalization. Processes data in its original format.
• Nominal: Normalizes data as deviation from engineering specification nominal. [(USL+LSL)/2]
• Target: Normalizes data as deviation from the target value specified in the specification limit record.
• Process Mean: Normalizes data as deviation from the process mean value specified in the current control limit record.
• Short Run: Normalizes data using short run data transformation.
• Standardized: Normalizes data using standardized data transformation.
• Estimate (Control Chart Processing): Plots an overlay line that represents an estimate of the current process condition.
EWMA: Provides an Exponentially Weighted Moving Average overlay where the weighting factor value determines how much historical data to include in the estimate. The smaller the Weight setting, the more significant the historical data is to the current point.
Running Average – Displays the running average overlay line. At any given plot point, the running average line represents the average of the current and all previous plot points. The most recent running average will always be equal to the calculated centerline.

Control Plans: Written descriptions of the systems for controlling part and process quality by addressing the key characteristics and engineering requirements.
Note: Convert and write the measurement data blocks as subgroups into the ProFicient database.
Cp – The ratio of tolerance to 6 sigma, or the upper specification limit (USL) minus the lower specification limit (LSL) divided by 6 sigma. It is sometimes referred to as the engineering tolerance divided by the natural tolerance and is only a measure of dispersion.
Cp and Pp – Assess variation relative to tolerance
Cpk and Ppk – Assess closeness of location relative to the nearest specification given the current level of variation.
CpK – The value of the CpK is the difference between the average of the measured values and the nearest specification limit (LSL,USL) divided by three times the standard deviation.
Equals the lesser of the USL minus the mean divided by 3 sigma (or the mean) minus the LSL divided by 3 sigma. The greater the CpK value, the better. Cpk is calculated using the within-subgroup estimate of the standard deviation Rbar/d2 (per ZMH-QMS-2-035-EN FINAL Statistical Techniques).
Critical Process Parameter (CPP): Measurable input (input material attribute or operating parameter) or output (process state variable or output material attribute) of a process step that must be controlled to achieve the desired product quality and process consistency.
Critical Quality Attribute (CQA): Physical, chemical, biological or microbiological properties or characteristics that should be within an appropriate limit, range, or distribution to ensure the desired product quality.
Note: CQA and CPP are input to InfinityQS
Critical to Quality (CTQ): Critical to Quality characteristics are product, service, and/or transactional characteristics that significantly influence one or more critical to satisfaction in term of quality. In regard to product, is an attribute of a part, assembly, sub-assembly, product, or process that is literally critical to quality or more precisely, has a direct and significant impact on its actual or perceived quality. These characteristics can be classified as CPPs, CQAs and CTSs.
Critical to Safety (CTS): Critical To Safety attribute which has the potential, directly or indirectly, to cause harm or injury to the patient, caregiver or service personnel.
CTQ: critical to quality (Critical “Y”) – Element of a process or practice which has a direct impact on its perceived quality.
Critical Observation – Critical observations could lead towards market action or regulatory action by a regulatory authority (e.g., recall or a withhold recommendation on pending applications). Critical observations describe a situation that has resulted, or has the potential to result in an immediate or latent health risk. A pattern of major observations or a repeat observation in the same system could lead towards elevation to a critical observation. Immediate remedial action must be initiated. Within fifteen (15) calendar days an action plan is to be available and approved to/by the Lead Auditor.
Critical Process Parameter (CPP) – A process parameter that can affect the critical quality attributes(s) of the process. These parameters are monitored during routine production to document that the process is operating in a state of control.
Critical Process Parameter Range -The acceptable range over which a critical process parameter can vary during routine manufacturing and still produce material with acceptable critical quality attributes. The critical process parameter range may vary from application to application depending on the unique requirements of an application.
CUSUM – Cumulative Sum plots are the cumulative difference of subgroup values from their target values.
Shewhart Style: Creates a Shewhart style CUSUM chart where the accumulated difference divided by the square root of the subgroup size is plotted.
Tabular (Decision Interval): Creates a Tabular CUSUM chart with positive and negative deviations plotted as separate lines.
Customer needs or expectations – Needs, as defined by customers, which meet their basic requirements and standards.
Data Entry Configuration – Listing of the rules used in the SPC data collection process; will include parts, processes, test characteristics, sample size, and any optional items deemed necessary to capture a meaningful sample.
Data Entry List View Options:
• Display Characteristics in a Single List (Display Options). ProFicient displays the desired characteristics in a single vertical list, and also automatically disables the Show all processes inside the Process option.
• Display Input for Test Comments (Display Options). ProFicient allows operators to type a comment (or note) for each test value during data entry.
Data Source – Identifies a connection to an Open Database Connectivity (ODBC) database and instructs ProFicient SPC or any Windows application what database to connect to and what tool or ODBC Driver to use to access the database.
Database Manager (DBM) – Utility used to manage ProFicient databases. DBM provides a graphical representation of a database and the tools necessary for creating and modifying individual records within the database.
Database Mgr – Import/export in DB: During initial migration: to move Dev to QA and then move QA to Dev. Only once, to prevent junk data. Validations are done in QA.
1. Database Dump: taking out data and saving into a file (entire database)
2. Database Load, always init database /destroys data: taking files that was dumped into a different database
3. Best choice: Import/export database structure ; not very good at modification ; if part already exists, system will ignore it, any modifications will not be imported; manually change a specified database object after import/export process; purpose: for daily backup
Data Type: There are two types of attribute data: defects and defectives.
Database Value Properties – Data Entry Configuration> Process/part/job data entry method> properties> database value
DCS – Data Collection Services consists of data collectors
The ProFicient Data Collection Service (DCS) imports process state, specification limit, and subgroup information into the ProFicient database using data acquired from the InfinityQS Data Management System (DMS). Once configured and running, DCS is a fully automated data collection utility that requires no user interaction.
Note: In DCS, there are data collectors that write the specific data from DMS directly to the destination (ProFicient database or IDEF file for EIS processing). PCDMIS test group is only used for the test names extracted from the XSTAT file by the PCDMIS DATA COLLECTOR.
• Process State Data Collector. The Process State Data Collector acquires process states from InfinityQS DMS and compiles them into ProFicient process states.
• Specification Limit Data Collector. The Specification Limit Data Collector acquires specification limits from InfinityQS DMS and compiles them into ProFicient specification limit.
• Subgroup Data Collector. The Subgroup Data Collector acquires live data from InfinityQS DMS and compiles it into ProFicient subgroups.
Defect measurement – Accounting for the number or frequency of defects that cause lapses in product or service quality.
Defectives – One of three types of tests used to measure or inspect a Part or Process. It refers to a binary condition; good/bad, pass/fail, go/no-go, typically used to count the number of defective pieces in a subgroup. Defective test values follow a binomial distribution.
Defective Codes
Sealing Defect
Welding, Soldering Defect
Adhesive, Bond Defect
Assembly or Connection Defect
Packaging Assembly Defect
Dimension Out of Spec
Geometry Out of Spec

Defects data – Must be part of defects group. Defects data are count data and are described in Poisson distribution.
Defects – Sources of customer irritation. Defects are costly to both customers and to manufacturers or service providers. Eliminating defects provides cost benefits.
Defects – One of three types of tests used to measure or inspect parts or processes. It refers to characteristics used to count the number of defects on a part, such as total number of imperfections found on a part. Defects data follow a Poisson distribution.
Defective data – the number of rejected parts in a lot as described with a bionomial distribution.
Descriptors – Provide additional traceability to a data value or subgroup of values. Sometimes referred to as Tag Fields. Common examples include Work Order Number, Vendor Name. ProFicient has six predefined super-descriptors: Shift, Job, Lot, Component Lot, Serial Number and Employee. A super-descriptor provides additional functionality. All other descriptors are called User-Defined Descriptors. There is no limit to the number of descriptors that can be associated to a subgroup.
DFSS (Design for Six Sigma) – A systematic methodology utilizing tools, training and measurements to enable us to design products and processes that meet customer expectations and can be produced at Six Sigma Quality levels.
DMAIC (Define, Measure, Analyze, Improve and Control) – A process for continued improvement. It is systematic, scientific and fact based. This closed-loop process eliminates unproductive steps, often focuses on new measurements, and applies technology for improvement.
DMS – Data Mgt Services
DMS as a Service – The DMS is a Windows service that runs when the computer boots, and the application does not require a logged in user or user interaction.
DMS Consumer – A Consumer is a software object that reads values from the DMS DataStore, and then writes those captured values into a database.
DMS Item – Managed by a Provider, an Item contains one value from the connected shop floor equipment. For example, if a Provider connects to a PLC and you were capturing X, Y, and Z positions from a servo controller, the Provider would manage three items (one for X, one for Y, and one for Z).
DMS Provider – A Provider is a software object that captures values from shop floor equipment using interfaces or links, and then places those captured values into separate Items.
DMS Provider Hierarchy – In the DMS system, there could be several Providers, and each Provider could be publishing several Items.
Dynamic value – Variable values
Dynamic Capability Report – The new capability report dynamically adds and removes rows based on the report’s master data selection. For example, if you configure the report’s data selection to include all rows for Active Data Entry Part, the entire report refreshes upon selecting a new part.
Dynamic Sampling Workflow – Incorporates workflow requirements at the shop floor level, allowing automatic prompting to operators when data collection is required. Shows a visual checklist to the operator, reminding them when HACCP, SSOP and other critical quality checks must be performed.
Edit Toolbar – The Edit toolbar command supports a new subgroup id (SID) argument. For example, >>edit(1,12345) will attempt to edit a subgroup in the Data Entry Configuration (1) with the subgroup id (SID) of 12345.
Ellipsis . . . (Browse to display a list of options) symbol used to get to the properties of an item in ProFicient; also can be synonymous to Browse for more options/functions like setting up properties of selected item as highlighted
Event – Anything occurring out of the ordinary pertaining to the software which requires an operator to change their regular operations. It can be triggered by a defect code, spec limit, alarms and other defined rules (see Event Types).
Type Name Event Time Process Part Test
Specification Limit >USL 3/16/2015 10:52 42511000410 SF + 0.8
Specification Limit >USL 3/18/2015 11:13 42511000410 O2 <= 0.5%
Specification Limit = 11in Hg
Specification Limit open job > related tables >double click to select a lot
Job Group – is used to categorize Job Data into logical groups; one job group consists of any number of job names and links all tables descriptors under one job group.
Job Operation describes each of the operations performed by a Job. Some fields within Job Operation records may not remain static. For example, job operation state can change from “Released for Test” to “Closed”.
Job Operation Process links Process Information to a Job Operation.
1. Lot: (the lot size that identifies how much parts being produced); Select: released for testing (so they can start working); set lot size
2. Part: parts being produced
3. Process (can be optional but w JDE integration, automatic work and lot order configuration)
4. Now you can use a job control operation in your process: saves user from selections
Jobs for Work Order – Job control data entry config: mapping jobs to Work Order (WO) ; same words; job WO; job or WO; Job in DB mgr
Linked Chart – Any chart that is linked to a Data Entry Configuration
Lot is defined as a definite quantity of an item produced under uniform conditions and passing as a unit through the same series of operations.
Lot size is required in setting up acceptance sampling configuration.
LSL – Lower Specification Limit; the lowest acceptable value for a characteristic of a part.
MIS – Measurement Inspection Sheets
Moving Range – The absolute difference between two consecutive individual values (IX).
ODBC – Open Database Connectivity is a Microsoft standard defining the way that applications and databases communicate. ProFicient application communicates with all database systems in a common language. The driver then translates the data into a language that the specific database system can understand.
OEE – Overall Equipment Efficiency data entered:
1. CPP critical process parameter
2. CQA critical quality attributes
3. CTQ critical to quality

Parametric Release – Declaration that product is sterile, based on records demonstrating that the process parameters were delivered within specified tolerances.
Pareto Chart – Graphical representation used to identify the most commonly occurring items within a dataset. The chart allows data to be split into major and minor categories. Also called a Pareto distribution diagram, is a vertical bar graph in which values are plotted in decreasing order of relative frequency from left to right. Pareto charts are extremely useful for analyzing what problems need attention first because the taller bars on the chart, which represent frequency, clearly illustrate which variables have the greatest cumulative effect on a given system.
Pareto diagram – Focuses on efforts or the problems that have the greatest potential for improvement by showing relative frequency and/or size in a descending bar graph. Based on the proven Pareto principle: 20% of the sources cause 80% of any problems.
Part is whatever you are producing that test can run into. It is the final result that you are measuring. It lists pressure set points and in JD Edwards consist of product names. Part represents what is being examined, observed or evaluated and can be distinguished from another by differences in geometric shapes, size, color, material, etc. In ProFicient parts are organized under different groups. Typically different parts have different specifications.
Part definition table lists part name, all parts are part of a part group
Part Group Table
Part Group Name
1432234172 FMT
1431545840 DATA COLLECTION PARTS
1431545839 TSV
1431545837 ANALOG
1431545831 ABUTMENT
1431545832 OBS
1431545830 Miscellaneous
1431102884 PKDMIS
1428528407 Water Type
1427400055 Generic Part
1425309662 PC-DMIS
1425309661 Articular Surface
Part Test Table
Part Test
42512000410 Instron Setup Dummy
42512000410 Seal Strength
42512000410 Gross Leak Detection
42512000410 Creep Test
42512000410 Sign Off
42512000410 Dummy
42512000410 CCL4 <= 2.0
42512000410 Water <= 4.0
42512000410 TOC <= 1.25 PRECISION MACHINING – A process where material is removed by a cutting surface – such as grinding, honing, turning, milling, etc. The process must be controlled in a manner that all variation (vibration, bearings, gage error) is statistically insignificant except tool wear. Other processes that exhibit very similar variation – Stamping can be one if the effect of lot to lot material variation (a special cause) is relatively small compared to the tolerance. You can tell if it is a candidate when you make the tool to one end of the spec to allow for wear over time. For CNC turning operations, the tool life may be one shift. For a stamping die (whether forming or punching) can have a very long life. But, the distribution is still the same – a rectangle. It is hard to prove with short term data – long term data is much more convincing. Ppm and % defective – Fraction of defective parts out of the total population of parts. Printable API Charts – Software developers using the ActiveX controls can now print the control chart, the capability chart, and the Pareto chart. For example, when you drop the chart into Microsoft VBA for Excel, print preview and print will display the graphic rather than an empty space. Process – Describes what creates treats or prepares the part being evaluated in the test. A process is typically a machine or operation. Many processes could be used to produce a finished part. Process mapping – Illustrated description of how things get done, which enables participants to visualize an entire process and identify areas of strength and weaknesses. It helps reduce cycle time and defects while recognizing the value of individual contributions. Process vs Cell – Process is the cell number (Process 200, multiple machines); produces the part that you will be making adjustments; identified by the machine types (n) Project – Each project is a file. To better handle projects with several charts, InfinityQS recommends creating more projects with fewer charts, and then creating toolbar commands to navigate between the projects. One Project – is equal to one cell or one manufacturing area. Other processes in the cell and other cells will have different projects (either dynamically = not separate or entirely separate). *.lPJ – IQS project file contains: 1. Data source to the database for data storage 2. Data type entered in database 3. Control charts 4. Specifications, raw data, table linkages Project – A “template” that describes what database to use, if and how subgroup information will be added, what charts to display, and may include requirements to respond to alarm conditions Range – Value calculated by subtracting the smallest value from the largest value within a subgroup. Raw database tables – If you are in raw database tables, part def (live data), part_def_t (audit data);both are shown when selected Root cause analysis – Study of original reason for nonconformance with a process. When the root cause is removed or corrected, the nonconformance will be eliminated. Sample size – the number of items in a single subgroup Acceptance Sampling Requirement Lot Table Part Process Test AQL Plan 2865304 Final Inspection 3 RIGHT HAND THD. LEAD 1 Zero Acceptance Number Sampling Plans.def 2050401 Final Inspection 3 RIGHT HAND THD. LEAD 2.5 Zero Acceptance Number Sampling Plans.def 2050401 Receiving Inspection 3 RIGHT HAND THD. LEAD 2.5 Zero Acceptance Number Sampling Plans.def Sampling plan types: • Variable sampling (continuous measurement, measured by mean and standard deviation) • Attributes sampling (Go/NoGo inspection, defects –number of defects per unit) ; IQS uses defectives to list defect types Note: Sampling, SPC and 100% inspection are output to InfinityQS SD – Standard Deviation. A measure of variation representing the average deviation of values about their mean. Set up sheets with specifications and set parameters in machine using set up sheet (CPPs). Set up spec for each part – Skip character if no test limit : test management (not all parts have same spec) Short Run – A term to describe a family of control chart options. The short run options include target, nominal, short run, standardized and group. Sigma – A statistical measure of variation (spread) Six Sigma – A vision of quality, which equates with only 3.4 defects per million opportunities for each product or service transaction. Strives for perfection. SPC Monitor -Spreadsheet-like window that allows configuration of each row with different Part, Process and Test characteristic combination. Each row is a control chart without the graphical display. Spec description vs Test description – Specification description overrides test description Special Cause Variation: Also known as “assignable cause variation,” is variation attributed to a special cause that is not inherent to the process. This is identified as a single data point observed outside of the control limit through the use of control charts, as defined by Rule 1 in the Western Electric rules. Specification Limits – Limits that determine the acceptability of a Test characteristic. Sometimes referred to as Engineering limits or Voice of the Customer, they are based on a part’s requirements, can be defined for any test and are unique for any Part / Test combination. Below is a sample data in a specification limits table: Part Test USL TAR LSL Cp Cpk Pp Ppk R+R Marginal R+R Maximum 42512200611 Burnt Seal 0 0 0 1.667 1.333 0 0 20 30 42521200512 Tears or Pinholes 0 0 0 1.667 1.333 0 0 20 30 Specified Control Limits Control limits that have been locked by the user – can be based on historical data or be user-defined. Specs and part definition table – Tab in part defiition table; tabs are windows into other tables (part,test) Stable Process – A process is stable if it does not contain any special cause variation; only common cause variation is present. Control charts and run charts provide illustrations of process stability or instability. Standardized – A chart processing option that plots points in terms of standard deviation units and has a centerline of zero and control limits of +3 and -3. Also known as a Z-chart. Static values – Unchanging values Statistical Process Control ( SPC) – A systematic method of tracking, predicting and reducing process variations. SPC involves sampling a process at regular intervals. Subgroups of the process are then analyzed to determine if the process is in statistical control and/or capable of meeting requirements. If the process is found to be out of control and/or not capable of meeting requirements, it is analyzed to determine the sources of unwanted variability. Once the sources of variability are determined, steps are taken to remove or reduce the variability in a process. Statistical process control – The application of statistical methods to analyze data, study and monitor process capability and performance. Subgroup data (SGRP_EXT) – contains the data entered in the IQS data entry menu Subgroup: A homogeneous sample of one or more pieces produced under the same set of conditions. Each subgroup is represented as a data point on the control chart for location and dispersion. Tables – list, safe for import, some tables should never be imported such as subgroup tables (5), Preferences > show all tables (74); 178 is listed (104 hidden from view are not editable, for construction
Target – The expected value of a reading as defined in the Specification Limit record. Also refers to a control chart processing option where the plot points are based on the deviation from the specification limit target value. Target processing is required when combining characteristics on the same chart that have different nominal or target values.
Test – May include measurements (includes +/- tolerance)
Test Group – PCB test group with database link
Test name (31 char) – Test number (properties of test + tolerance)
Test – Name of a characteristic or feature that is being measured. Test value represents the outcome of the examination, observation or evaluation being performed.
Test_DAT – Test definition table contains the following information defined using the Database Manager utility of InfinityQS
Type Name
Defectives Tears or Pinholes
Variable Test Duration
Variable TOC <= 1.25
Variable Top Setup Completed
Variable Total Organic Carbon
Variable Vacuum Pressure
Variable Water <= 4.0 Tree diagram – Graphically shows any broad goal broken into different levels of detailed actions. It encourages team members to expand their thinking when creating solutions. U Chart – Control chart used for monitoring defects from varying subgroup sizes. A u-chart plot represents the average number of defects for the subgroup. USL – Upper Specification Limit; the largest acceptable value for a characteristic of a part. Variables – One of three test types used to measure or inspect a Part or Process. A variable test is one that can be measured on a continuous scale. List of Variable and Attribute test in the Test Definition Table Type Name Defectives Adhesive Transfer Defectives Bubble Test Defectives Tears or Pinholes Variable Drill PT. OPT. Variance – A change in a process or business practice that may alter its expected outcome. Windows Authentication and LDAP Authentication – From Database Manager, the Policy Settings have been updated to support Windows Authentication and LDAP Authentication. After enabling this policy, ensure that the employees have appropriate privileges, and that their ProFicient Sign In Name matches their Windows or LDAP Sign In Name. Workstation and project file – Each workstation is linked to a specific project file with navigation into projects (site > CMM > machining, etc) and is accessed based on user permissions.
Xbar – A sample’s or dataset’s mean value. X-bar is an estimate of a population’s mean. Calculated by taking the average of a representative data.
XDAT PCD File – contains many tests data; data collectors; not readable ; use PCD data collector to sort data