A free online reference for statistical process control, process capability analysis, measurement systems analysis, control chart interpretation, and other quality metrics.
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The risk of being wrong when completing a hypothesis test.
The chi-square table is computed in such as way that if the assumption of “normal data” is true for a given X-bar and sigma, the results of the chi-square test will be incorrectly rejected only 5% of the time. This calculation reflects the alpha value.
An assignable cause is a source of variation that is intermittent, not predictable. It is sometimes called “special cause” variation. On a control chart, an assignable cause is signaled by points beyond the control limits or nonrandom patterns within the control limits.
Attributes data is data that can be classified and counted. There are two types of attributes data: counts of defects per item or group of items (nonconformities) and counts of defective items (nonconforming). For example, yes/no, good/bad, pass/fail, and go/no go.
Another term for a mean, it is an indicator of the center of a set of data points. It is found by adding all the individual values and dividing by the number of values.
Another term for the shape formed by a normal distribution when drawn as a histogram.
Something that influences the selection of certain items when collecting a sample.
A distribution that has two modes. Drawn as a histogram, this condition is reflected by two peaks or high points.
The capability of a process is how the process performs when compared to specification limits or requirements. It uses a series of indices: Cp, Cpk, Cr, and Cpm.
A set of statistical calculations performed on a set of data to assess how the distribution formed by the data compares to specifications or requirements.
A process is said to be capable if nearly 100% of its output falls within specification limits.
An attributes control chart that is used to monitor the number of nonconformities, such as defects per subgroup. The subgroup size must remain constant for this type of chart.
Central location is the center of a set of data points. Mean, median, and mode are the statistics used to describe it.
Statistics such as the mean, median, and mode are said to be measures of central tendency.
A distinguishing feature of a process or its output on which variables or attributes data can be collected.
A goodness-of-fit-test statistic used to test the assumption that the distribution of a set of data is similar to the expected distribution, such as a normal distribution.
A ratio that measures the significance of the standard deviation in relation to the mean.
A source of variation that is inherent in a system and is predictable. A control chart identifies a system with only common causes of variation. Common causes of variation affect all individual values of a system, and can be eliminated only by a systemic change.
A control chart is a graphical representation of a characteristic of a process, showing plotted values of some statistic, a central line, and one or two control limits. It is used to determine whether a process has been operating in statistical control and is an aid to maintaining statistical control.
Lines on a control chart used as a basis for judging whether variation in data on a chart is due to special or common causes. These limits are calculated from data collected from the system, they are not specifications or limits set by customers or management.
A capability index that compares the width of a two-sided specification with the variation in the process. Estimated standard deviation is used to calculate the process variation. A Cp larger than 1 indicates that the process variation is narrower than the specification.
Cpk is a capability index that tells how well a system can meet two-sided specification limits. Because it takes the target value into account, the system does not have to be centered on the target value for this index to be useful. It is calculated with estimated standard deviation. A Cpk greater than 1 indicates that the process can meet the specification.
A capability index that compares the variation in the process to the lower specification. Estimated standard deviation is used to calculate the process variation. A Cpl greater than 1 indicates the process is capable of meeting the lower specification.
Cpm is a capability index that shows how well the system can produce output within specifications while taking the target into account. Its calculation uses sigma calculated from the target value instead of the mean.
A capability index that compares the variation in the process to the upper specification. Estimated standard deviation is used to calculate the process variation. A Cpu greater than 1 indicates the process is capable of meeting the upper specification.
Capability ratio compares the variation in a process with the width of a two-sided specification. Estimated standard deviation is used to calculate the process variation. It is the inverse of Cp.
An occurrence such as a blemish, scratch, burn, error, or omission that appears on an object. A defect does not necessarily make the object unusable or unacceptable.
A product or service flawed beyond use or acceptability.
This refers to a description of the capability of a measurement system.
Statistics such as the range and standard deviation (sigma) are said to be measures of dispersion.
Distribution is a way of describing the output from a system of variation. The distribution’s location, shape, and spread may be evaluated by statistics such as the mean, median, sigma, and range.
This is an estimate of the standard deviation calculated by dividing the average range by the tabular constant d2 (R-bar/d2).
A histogram is a bar chart that represents the frequency distribution of data. The height of each bar corresponds to the number of items in the class or cell. The width of each bar represents a measurement interval. The histogram shows basic information such as central location, shape, and spread of the data being examined.
A process is said to be “in control” or “stable” if it is in statistical control. If a process is in statistical control, a control chart will have no subgroups falling outside the control limits, no runs, and no nonrandom patterns.
The individual portion of an X-MR control chart. The individual data points are plotted onto the chart and compared with control limits.
Kurtosis is a statistic that is used to measure the “flatness” or “peakedness” of a set a of data. It represents a measure of the combined weight of the tails relative to the rest of a distribution. As the tails of a distribution become heavier, the kurtosis will increase. As the tails become lighter, the kurtosis value will decrease.
A line on a control chart used as a basis for judging whether variation from the data on the chart is due to special or common causes. Any point beyond the lower control limit is an indication of a special cause occurring. This limit is calculated from data collected on the system, it is not a specification or limit set by customers or management. The symbol is LCL.
The lower limit of a specification. This limit is set as an aim for a system or process, it is usually set by the customer of the process, engineering, or management. The symbol for the lower specification is LSL – lower specification limit.
When a varying sample size is being used in a p or u-control chart, the maximum acceptable sample size is usually a sample size that is twenty-five percent larger than the average sample size. Any subgroup with a sample size larger than the maximum acceptable subgroup size has to have control limits calculated specifically for that subgroup.
Another term for average, it is an indicator of the central location of a set of data. It is found by adding all the individual values and dividing by the number of values.
A measurement system consists of the people, procedures, systems, and devices used to take measurements.
The middle number in a set of data when it is ranked from lowest to highest, it is an indicator of central location in a data set.
When a varying sample size is being used in a p or u-control chart, the minimum acceptable sample size is usually a sample size that is twenty-five percent smaller than the average sample size. Any subgroup with a sample size smaller than the minimum acceptable subgroup size has to have control limits calculated specifically for that subgroup.
Is the number that occurs most frequently in a data set. It is usually an indicator of central location.
The difference between consecutive subgroup values on an X-MR control chart. The moving range is used as a measure of variability.
The moving range portion of an individuals and moving range control chart. The moving ranges are plotted on the chart and compared with control limits.
A distribution of data where most of the data appears on the right hand side of the distribution and then tails off to the left. Also known as a skewed left distribution.
Nonconforming data is a count of defective units. It is often described as go/no go, pass/fail, or yes/no, since there are only two possible outcomes to any given check. You can track either the number of defective units or the number of nondefective units.
Nonconformities data is a count of defects per unit or group of units. It can refer to defects or occurrences that should not be present but are, or any characteristic that should be present but is not.
Data that does not form a normal distribution.
Any data set that does not show a normal, bell-shaped distribution.
A pattern in data that is repeating, or is not due to normal variation.
This bell-shaped curve is used to illustrate the shape of a normal distribution.
A data distribution that is bell shaped and symmetrical, the normal distribution is the basis for control chart and capability analysis.
A normal probability plot is a graphical method for showing a frequency distribution. The scaling is set up so that if the distribution is normal, a straight line will result.
An attributes control chart that plots the number of items that are defective or possess a characteristic of interest. The subgroup size must remain constant for this type of chart to be used.
An observation is a single piece of data, usually a count or a measurement. It is also known as a reading.
When applied to data collection, it is a clear, concise, and detailed definition of a measure. It ensures that those collecting data do so consistently.
An outlier is a point on a chart that does not fall into the pattern of the rest of the data.
When applied to a control chart, out of control means that at least one special cause of variation is present.
Over reaction to a set of data. For example, in a control chart, it would be reacting to a common cause as if it were a special cause.
A Pareto chart is a bar chart for ranking aspects of a problem. Typically, a few aspects make up a significant portion of the problem while many trivial aspects exist.
An attributes control chart that plots the number of items possessing a characteristic of interest. The subgroup size may vary.
A distribution of data where most of the data appears on the left hand side of the distribution and then tails off to the right. Also known as a skewed right distribution.
Pp is a capability index, similar to Cp, that is a measure of process performance. Pp tells how well a system can meet two-sided specification limits, assuming that the average is centered on the target value. It is calculated with the actual sigma (using the actual individual values) rather than the estimated sigma. A Pp larger than 1 indicates that the process variation is narrower than the specification.
Similar to Cpk, Ppk is a capability index that indicates whether a process is capable of meeting two-sided specification limits. However, Ppk uses actual standard deviation to calculate the process variation, whereas Cpk uses an estimated standard deviation. The target value is taken into account with Ppk, so the system does not have be center on the target value to be useful. A Ppk greater than 1 indicates that the process can meet the specification.
A capability index similar to Cpl in that it compares the variation in the process to the lower specification. However, Ppl uses standard deviation to calculate the process variation, whereas Cpl uses an estimated standard deviation. A Ppl greater than 1 indicates the process is capable of meeting the lower specification.
A capability index similar to Cpu in that it compares the variation in the process to the upper specification. However, Ppu uses standard deviation to calculate the process variation, whereas Cpu uses an estimated standard deviation. A Ppu greater than 1 indicates the process is capable of meeting the upper specification.
A capability ratio similar to Cr in that it compares the variation in a process with the width of a two-sided specification. However, Pr uses standard deviation to calculate the process variation, whereas Cr uses an estimated standard deviation. It is the inverse of Pp.
A process is the combination of people, equipment, materials, methods, and environment that produce output—a given product or service. The words process and system are often used interchangeably.
Process capability is the 6 sigma range of common cause variation for statistically stable processes only. Sigma is usually estimated by R-bar/d2.
The process performance is the 6 sigma range of inherent variation for statistically stable processes only, where sigma is usually estimated by the sample standard deviation.
A distribution that forms no particular shape.
A sample that allows every item in a population to have an equal chance of being selected, with no bias.
Range is an estimate of spread in a set of data points; the difference between the highest and lowest values in the data set.
Repeatability refers to variation in a series of measurements that have been taken with one gage measuring one characteristic of the same item by the same person.
Reproducibility refers to variation in a series of measurements that have been taken with one gage measuring one characteristic of the same item by different people.
A run chart is a simple line chart that plots one characteristic over time. It is used to plot individual observations and detect patterns in the data.
A sample is a collection of one or more observations used to analyze the performance of a process, as opposed to the total populations. It is intended to represent the characteristics of the population. Sample is a synonym for “subgroup” in process control applications.
The number of pieces of data taken at one time. For example five boxes are checked for stiffness every hour, the sample size in this case is five. If the temperature of a room is taken every hour, only one number is collected every hour, so the sample size is one.
Sigma of the individuals is standard deviation calculated from the individual data values in a data set. It is also known as actual or calculated sigma.
Sigma is the Greek symbol, , used to denote standard deviation. It is a measure of the variation or spread within a set of data.
A distribution that tails off to one side, either to the left or right.
Skewness is a statistic that is used to measure the symmetry of the distribution for a set of data. A process that is skewed tails off to the left or to the right.
Special cause variation is a source of variation that is intermittent, not predictable. Sometimes it is called “assignable cause” variation. On a control chart, a special cause is signaled by points beyond the control limits, runs, or nonrandom patterns within the control limits. A process that has special cause variation is said to be out-of-control, unstable, or unpredictable.
Specifications are boundaries, usually set by management, engineering, or customers, within which a system must operate. They are sometimes called engineering tolerances.
Spread is the range of data from the lowest value to the highest value.
A system, analysed by a control chart, with no special causes of variation present, this system is also said to be in control. Variation within a stable system is due to common causes, and is predictable.
A statistic that describes the variation or spread within a data set. It can be used to indicate the variation in a process and to compare with specifications.
Statistical control is a condition describing a process from which all special causes of variation have been removed and only common causes of variation remain. On a control chart, processes that are in statistical control show no subgroups outside the control limits, no runs, and no nonrandom patterns. This condition is also referred to as in control, stable, or predictable.
A subgroup is one or more occurrences or measurements taken at one time. Multiple subgroups are used to analyze the performance of a process. Subgroup is used as a synonym for “sample.”
A distribution that if cut in half, shows each side is the mirror of the other.
The exact value at which customers, engineering, or management want the system to operate.
On a control chart, trial limits are calculated when there is insufficient data to calculate control limits. These give a temporary guide until sufficient data has been collected.
An attributes control chart that is used to monitor the number of nonconformities per unit, such as defects per item. The subgroup size may vary.
Not reacting to a set of data when the data is showing an issue or problem. For example, in a control chart, it would be ignoring a special cause of variation.
A distribution, when drawn as a histogram, has each bar at a similar frequency.
A system that contains special and common causes of variation; this system is also said to be out of control. An unstable system is unpredictable.
A line on a control chart used as a basis for judging whether variation from the data on the chart is due to special or common causes. Any point beyond the upper control limit is an indication of a special cause occurring. This limit is calculated from data collected on the system, it is not a specification or limit set by customers or management. Its symbol is UCL.
The upper limit of a specification. This limit is set as an aim for a system or process, it is usually set by the customer of the process, engineering, or management. The symbol for the upper specification is USL–upper specification limit.
Variability refers to the differences among individual outputs of a process. In control chart pairs, it refers to the differences between individual observations and is analyzed in range, sigma, and moving range charts.
Variables data is data that is acquired through measurements, such as length, time, diameter, strength, weight, temperature, density, thickness, pressure, and height. X-bar and range, X-bar and sigma, and individuals and moving range charts are used to analyze variables data.
Variation is the inevitable differences that occur among individual outputs of a process. Sources of variation may be grouped into two major categories: common causes and special causes.
X-bar is the average or mean of values in a group of observations.
The X-bar chart is a variables control chart that shows the subgroup averages. The subgroup size for this chart must be larger than one and consistent.
The symbol for the Z value for the lower specification limit. It represents the number of standard deviations between the average and the lower specification limit.
The minimum of the Z values, either Zupper or Zlower. It is used to calculate the Cpk index in capability analysis.
The symbol for the Z value for the upper specification limit. It represents the number of standard deviations between the average and the upper specification limit.
Used in capability analysis, it is the symbol for the number of standard deviations between the average and a specification limit for a normal distribution.
A resource of data collection tools, including how to collect data, how much to collect, and how frequently to collect it.
Tools for analyzing and interpreting data so that the areas to improve become apparent.
Formulas for calculating control limits, capability indices, and more, plus the tables referred to in these calculations.
This complete glossary of quality tools, symbols, and abbreviations includes definitions for more than 200 quality terms.
Links to other quality resources.
For decades, PQ Systems has delivered reliable statistical quality and production control tools to help manufacturers ensure quality and compliance.
PQSystems SPC and Gage Management solutions empower you to maintain high standards and achieve operational excellence.
A free online reference for statistical process control ,process capability analysis, measurement systems analysis, control chart
PQ Systems provides intuitive solutions to help manufacturers optimize process performance, improve product quality, and mitigate supply chain risk. Simple and intuitive, yet accurate and complete, our solutions will help you achieve quality improvement success. PQ Systems SPC and gage management quality improvement solutions are relied on across an array of industries, ranging from aerospace to healthcare.
Harness the power of data analysis to increase customer satisfaction, improve audit success, and meet quality compliance requirements with statistical process control (SPC) software. PQ Systems delivers a robust SPC application that will help you easily analyze your data, understand and improve your processes, and communicate important quality information. Whether it’s for use on a single line or in a global multi-site operation, we provide a scalable, easy-to-use software solution to help you optimize quality that is simple to deploy, implement, and operate. Features include:
Stay organized and maintain gage inventory, measurement systems analysis (MSA) study results, calibrations, and certificates—all in one place. PQ Systems is a complete calibration management solution that provides easy access to all of your gage information including usage, calibration schedules, procedures, history, and more. This gage tracking software will help audit-proof your measurement system and give your team complete device traceability and precise calibration records.
Our gage management software is designed to save time and mitigate risk by organizing and managing your measurement system information. The audit trail maintains a robust and precise record of changes to gages and events to comply with industry standards. Features include:
At Advantive, our team of SPC experts are dedicated to helping manufacturing clients improve their quality processes and get the maximum return on their software investment. With more than three decades of experience in quality improvement, we know the problems and challenges you face and provide the flexible solutions, quality improvement consultations, hands-on training, and unrivaled customer service you need to succeed today.
Learn how Honeybee Robotics uses PQ Systems to support its gage management system and comply with ISO and AS auditors.
Before manufacturers can improve quality, they need to measure. At Advantive, we offer statistical quality control (SQC) software to monitor and manage quality across your shop floor—ensuring that each product meets regulatory requirements and customer specifications. Although similar to SPC software, our SQC tools measure outputs instead of inputs and provide the essential data that leaders need to make process improvement decisions.
To continuously improve manufacturing processes and minimize variability during production, SQC software gathers data from a specific sample size of a product and analyzes its performance statistics. By monitoring process outputs, our real-time SQC system helps you understand production value and can change the way you approach quality.
SQC software enables the collection of relevant, meaningful quality data in real-time at specific points along the production or assembly line. Line operators and plant floor managers can also access this detailed data in real-time to make instant adjustments to the quality of products.
To meet the diverse needs of manufacturing quality control, our SQC software includes different methodologies to monitor and maintain the quality of products. One method of SQC is acceptance sampling, which can be used to randomly inspect a sample of goods. A decision is made to accept or reject a batch of goods based on the results of the sample.
Another method of SQC is statistical process control (SPC), which uses graphical charts or visuals to determine whether a process should be continued or adjusted to achieve desired quality. SPC control charts are foundational quality control tools and figure prominently in Lean manufacturing and Six Sigma efforts. Control charts are used in a variety of ways, but on the shop floor, operators use them as a means of assessing, controlling, and ensuring the consistency of manufacturing processes. By controlling processes, operators can minimize significant process changes that can result in off-quality products. Our highly configurable control charts will ensure that you have the best control chart for detecting the right type of variation, resulting in reduced defects and greater process consistency.
Data collected over time can be rolled up and accessed through a centralized unified data repository, enabling quality professionals and facility supervisors to meet some of the most important objectives of statistical quality control: supporting continuous improvement over time and revealing opportunities for cost savings, reduced waste, improved workflow, and greater efficiencies. At the top level, Six Sigma professionals and executives can use historical SPC data for predictive analytics, comparing quality control data across lines, products, processes, and sites to determine where performance is highest–and where improvements can yield dramatic improvements in profitability.
We have made numerous investments in technology to help support our quality initiatives, and InfinityQS SCS allows us to bring everything together. We can now assimilate data from different systems and device locations into one centralized hub for easy analysis and decision-making.
President and COO
InfinityQS was the piece we needed to elevate our already strong processes and move toward manufacturing targets. We run to target because that is what our consumers want—and because it costs the company less due to the efficiencies SPC creates.
Quality Manager
The addition of InfinityQS to SanDisk’s existing system infrastructure gives us a significantly more responsive and effective production environment. InfinityQS has proven vital in resolving issues we didn’t even know we had.
Regional CIO
Find out how our customers are improving manufacturing processes and product quality with flexible quality management software from Advantive.
Advantive delivers actionable, problem-solving software solutions for specialty manufacturers and wholesale distributors that simplify processes, optimize performance, and increase revenues.
Product quality can make or break your manufacturing company’s success. That’s why you need a reliable quality management system (QMS) in place. At Advantive, our QMS solution provides a formalized platform that accurately tracks product specifications, documents processes, manages industry regulations, and helps you consistently meet quality standards.
At Advantive, we focus on providing accessible technology that drives transformational outcomes for manufacturers. Our specialized quality management systems include the tools and functionality you need to collect, test, and inspect products, meet customer and regulatory requirements, and ultimately, produce the highest quality products.
Our quality management software is integrated throughout your entire manufacturing facility to provide complete operational visibility. As information flows from one department to another, decisions can be made automatically to improve quality, productivity, on-time delivery, efficiency, and more.
Manage quality test requirements and results locally, regionally, and corporate-wide with our flexible QMS software.
Improve internal compliance with QA test plans and ISO requirements. If tests are skipped or results are not recorded, notification is recorded accordingly. When jobs are completed, documentation of results (including COCs and COAs) can be printed and/or emailed to appropriate parties. Because accurate results are recorded directly on the factory floor, you have the ability to respond to customer complaints and product returns with factual data. Having access to test results in real time also enables quality managers and others to examine and evaluate test results prior to shipping inferior products.
Optimize and reduce raw material and finished goods inventory. Eliminate costly material outages. Analyze what-if scenarios and market trends using multi-plant and corporate forecasts. Plan a group of similar production facilities or regional plant groupings to analyze and optimize material usage. Utilize tactical and strategic planning tools to manage long-term business strategies and more.
By utilizing InfinityQS to implement SPC and Six Sigma best practices across our manufacturing processes, Ben & Jerry’s will continue to identify opportunities for cost savings and ensure the highest level of customer satisfaction. The result is the perfect pint for our customers.
Quality Supervisor
I would recommend PQ Systems to any company that needs to gain control over their gage measurement system and have the confidence to be in compliance when it comes to ISO and AS auditors.
Facility Manager
Find out how our customers are using quality management software to improve product quality, decrease risk, and make strategic data-driven business decisions.
Today’s electronics manufacturing industry is highly competitive, with a continual need to produce high quality products while driving down costs. As a result, electronics manufacturers need real-time visibility–within plants and across the globe–to proactively maximize yields, lower costs, reduce scrap and waste, and ensure part and product traceability.
Keep up in this fast-paced and dynamic market space while improve your most pressing electronics quality control challenges. At Advantive, we offer specialized electronics manufacturing software to help suppliers and manufacturers comply with industry and customer standards for quality, consistency, and security. Our solutions can stand up to third-party audits, reduce product defects and variations, and drive continuous improvement with features like:
Find full traceability for any modification, edit, or change to any database record. When enabled, traceability records are easily viewed in various ways, but cannot be edited. Whenever a record modification or deletion is attempted, the “Reason for Change” tracking feature forces users to select a reason for the modification from a drop-down list and also requires a free-form comment. A Change History and Reason for Change Report can accompany any chart printout when specified.
Take proactive steps to prevent recalls, significantly reduce the time and costs of recalls in the event they occur, and standardize processes, documentation, and reporting with track-and-trace lot genealogy solutions across your entire supply chain. This functionality allows electronics OEM and tier suppliers to track raw materials or component lot codes throughout manufacturing operations and provide a complete view of the incoming/outgoing product relationship complete with statistical summary information. These reports allow you to determine:
Our manufacturing electronics software includes strict access control features to support requirements for electronic signatures including password aging, recycling, lockouts, length, and encryption. The security violation logs track and report security violations by individual users and their locations., while access logs track individual user access into and out of applications. We also offer audit trail logging, which provides a history of all changes made to any database record including sample data limits, alarm rules, change history, metadata, specification limits, and control limits.
In a highly regulated industry like electronics manufacturing, you need software that will help you easily track parts and products, meet specific requirements, and stand up to third-party audits. Advantive’s electronics ERP and SPC software boasts helpful built-in quality checklists, real-time data collection, and workflow alerting features needed to comply with these stringent manufacturing standards. This enhanced level of supplier monitoring and accurate data visibility can help quality control managers:
Learn how a Fortune 500 electronics manufacturing company achieves real-time insights and intelligence across its vast global manufacturing base with InfinityQS SPC software.
In highly regulated industries like medical device and pharmaceuticals, products must be of the highest quality to meet customer demands for safety and efficacy. With Advantive’s robust medical and pharmaceutical ERP and SPC software, we can help you improve product quality while meeting stringent government regulations.
Keep manufacturing processes operating at the highest efficiency with our flexible medical device and pharmaceutical ERP and SPC solutions. With built-in medical quality control and supplier monitoring functionality, our software helps medical device and pharmaceutical manufacturers comply with government regulations and industry standards for quality and safety. Core features include:
Use access logs to track individual user access into and out of applications, and track and report security violations by individual users and their location with security violation logs. Advantive’s strict access control features support all of FDA 21 CFR Part 11 technical requirements for electronic signatures including password aging, recycling, lockouts, length, and encryption.
Track raw materials or component lot codes throughout manufacturing operations with our powerful lot genealogy and reporting tools for medical device and pharmaceutical manufacturers. These reports allow you to determine:
Built-in checklists and workflow-alerting features help medical device and pharmaceutical manufacturers easily comply with Hazard Analysis and Critical Control Points (HACCP), Standard Operating Procedures (SOP), Critical Quality Attributes (CQAs) and Critical Process Parameters (CPP). With our powerful quality management solutions, you can also set reminders of when to perform HACCP, SOP, and other critical quality checks by incorporating workflow requirements at the production floor level and using our real-time dynamic scheduler, which offers visual checklists to operators.
Manufacturers in the pharmaceutical industry must also comply with FDA, U.S. Pharmacopoeia (USP), or other international Pharmacopoeia requirements for Net Weight Control and Content Uniformity. The Net Weight Control feature supports Pharmacopoeia Weight Variation and Content Uniformity requirements; in addition, our software provides related documentation and reporting to support the needs of global manufacturers.
We provide test cases, validation scripts, and validation services so that medical and pharmaceutical manufacturers can perform full, functional verifications of their software installations. These scripts provide a solid foundation for clients to validate our SPC quality system internally.
Additionally, we maintain a comprehensive statistical validation of our SPC software products to ensure the accuracy and validity of the calculations performed within. This statistical validation is performed by our staff of degreed industrial statisticians and made available in electronic format suitable for inclusion by our FDA-regulated clients in their own validation documentation. This data helps maintain efficient medical quality control in a global supply chain.
Learn how the world’s leading producer of implantable hearing devices improved quality control and increased real-time visibility across production with InfinityQS SPC software.
With the continual demand for shorter production cycles and high-quality products in an increasingly complex global supply chain, aerospace and defense original equipment manufacturers (OEMs) and tier suppliers manufacturers need real-time visibility—within plants and across the globe—to proactively increase quality through continual improvements, prevent and respond quickly to recalls, and ensure certification compliance.
Advantive’s world-class ERP and SPC solutions feature built-in tools and real-time visibility to support aerospace and defense manufacturers in meeting third-party (IAQG) audits, and government and industry standards for traceability, quality, safety, and compliance. Core industry-specific features include:
This feature provides full traceability for any modification, edit, or change to any database record when enabled. Traceability records are easily viewed in a variety of ways, but they cannot be edited. Whenever a record modification or deletion is attempted, the Reason for Change tracking feature forces users to select a reason for the modification from a drop-down list. Free-form comments are also required. When specified, a Change History and Reason for Change Report can accompany any chart printout.
Automated audit trail logging provides a history of all changes made to any database record including sample data limits, alarm rules, change history, metadata, specification limits, and control limits. This strict access control feature supports requirements for electronic signatures including password aging, recycling, lockouts, length, and encryption. The Security Violation Logs track and report security violations by individual users and their locations. Access Logs also track individual user access into and out of applications.
Auditing just became a lot easier with instant access to real-time quality records and electronic documentation needed to demonstrate compliance. This robust solution can stand up to third-party (IAQG) certification audits or internal audits for Quality Management Systems (QMS) that require ISO 9001:2008, AS 9100C:2009, EN9100:2009, and JIS Q 9100:2009. With built-in checklist- and workflow-alerting features needed to comply with QMS SPC requirements for key product characteristics, Critical Quality Attributes (CQAs), and Critical Process Parameters (CPP), creating reports takes only minutes instead of hours or days, eliminating the need for spreadsheets.
Automotive suppliers and manufacturers can track raw materials or component lot codes throughout manufacturing operations that support AS 9100C:2009 7.5.3 traceability requirements. Gain a comprehensive view of the incoming/outgoing product relationship, complete with statistical summary information with lot genealogy reports. For investigation purposes, genealogical “trees” can be created for any lot. These reports allow you to determine:
The food and beverage industry faces unprecedented regulation as consumers and governments worldwide demand high levels of safety and quality control for food, including “farm-to-fork” and “boat-to-plate” traceability. To help meet these demands, Advantive offers flexible ERP, SPC, WMS, and MES solutions specifically built for food and beverage manufacturers, from small independent manufacturers to large multinational players.
To maximize profits while improving enhancing food safety monitoring and control, Advantive provides food and beverage ERP and SPC software solutions to modern food manufacturers worldwide. Our highly specialized manufacturing systems are designed to help you streamline processes, reduce inventory, gain real-time visibility from your suppliers, co-packers, and third-party producers, and increase your bottom line. Core features include:
Paper and spreadsheets can no longer get the job done given today’s need for real-time and accurate quality data that is visible from the production floor to the corner office. With Advantive’s food and beverage software, you get a single solution to automate key data entry processes and simplify the way you collect data to provide complete transparency across your entire operations.
Modernize your production with Advantive’s world-class WMS and MES software designed for food and beverage processors. From produce to proteins to multi-ingredient, our solutions help you automatically connect to scales and palletizers to bring floor data to the office. Our food and beverage manufacturing software not only offers a clear vision of your production flow but also fortifies inventory tracking through in-process steps and refines your production process via yield tracking, catchweight production scheduling, and recipe management.
Streamlining warehouse operations is the cornerstone of every implementation of Advantive’s food and beverage manufacturing software. The software efficiently scans crates, boxes, or entire pallets directly into your inventory and swiftly checks them into their designated location. It provides real-time tracking of available ingredients and finished goods, as well as their exact whereabouts. To further enhance efficiency, our system incorporates automatic FIFO management and GS1 labeling to ensure smooth lot tracing processes.
Make auditing and compliance simpler with lot genealogy and traceability, simplified auditing, and complete visibility into the entire manufacturing lifecycle. Easily track raw material (ingredients) lot codes throughout the your entire food and beverage manufacturing operations. For investigation purposes, genealogical “trees” can be created for any lot. These reports allow you to determine:
Report with confidence using built-in tools that help food and beverage manufacturers comply with government regulations and industry standards for food quality and safety. Our world-class manufacturing solutions boast built-in checklists and workflow alerting features needed to comply with Hazard Analysis and Critical Control Points (HACCP) and Sanitation Standard Operating Procedures (SSOP). You can incorporate workflow requirements at the shop floor level, providing automatic data collection prompts to operators. We also offer a real-time Dynamic Scheduler which provides visual checklists to operators, reminding them when to perform HACCP, SSOP, and other critical quality checks.
When enabled, database auditing provides full traceability for any modification, edit, or change to any database record. Traceability records are easily viewed in a variety of ways, but they cannot be edited. Whenever a record modification or deletion is attempted, the Reason for Change tracking feature forces users to select a reason for the modification from a drop-down list. Additionally, free-form comments are required. When specified, a Change History and Reason for Change Report can accompany any chart printout.
Manufacturers in the food and beverage industry must also comply with filling requirements for Net Content Control (i.e., weight). Our solutions include a Net Content Control feature to support both the U.S. Department of Commerce Maximum Allowable Variation (MAV) and European Union Tolerable Negative Error (TNE) and T1/T2 requirements, plus related Net Content Control reporting to support the needs of global manufacturers. Many of our food and beverage manufacturing customers see fast ROI based solely on reduced “giveaway” or overfilling of product using the Net Content Control functionality.
Advantive’s food and beverage manufacturing software comes equipped with an intuitive reporting suite for instant, up-to-date visibility into your business operations. With several pre-designed reports and easily customizable reporting to fit your comprehensive MRP requirements, our food and beverage solutions integrate with your existing ERP system to deliver valuable insights that boost operational agility, execute virtual recalls in mere minutes, and provide transparency throughout your factory.
Fully IoT enabled, Advantive’s WMS and MES solutions for food and beverage manufacturers can integrate with your connected scales, inline printers, labelers, and even advanced robotics. Whether they’re in your plant now or part of your future vision, our production software accommodates your needs. At Advantive, we partner with trustworthy, innovative hardware solutions providers, from mobile printers to RF technology.
Learn how a global food and beverage manufacturer increased visibility and improved every step of their manufacturing process using InfinityQS SPC software.