Accuracy and precision define your capability for excellence
During recent decades, manufacturer and consumer expectations for product quality have continued to creep higher and higher. A world of customers on the always-connected internet has contributed greatly to this awareness.
Control charts provide a data driven view of your process. This promotes action based on evidence and reduces changes driven by worker observations of outputs that might not be relevant or significant.
Proper control chart selection is critical to realizing the benefits of Statistical Process Control.
While enormous dollars are spent reacting to problems, taking a top-down view of the production system can reveal sources of scrap, rework and other inefficiencies.
WinSPC can be configured for optimal use in practically any production or inspection set up.
It’s not subjective: Because it’s an objective measure of variation, standard deviation is an essential statistical tool for increasing quality.
In an ever-competitive global marketplace, it’s more important than ever to develop systematic means to measure and manage costs of quality, which reflect business improvement opportunities.
Before applying statistical methods that assume normality, it is necessary to perform a normality test on the data.
What is the difference between subgroup size, subrange size, and sample size in WinSPC? You will find the answer to that question in this article.
You’ve identified a new system that will improve quality. Now, you need to show management a compelling financial ROI and get buy-in. Here’s how to gain support for your proposal.
There is a balance between automation, and feedback. If you totally remove the operators away from the feedback of periodic measurements, they may be less aware of the nuances of the process over time.
When something goes wrong, we naturally react. If a product fails or a process performs inadequately, we attempt to discover what’s wrong so we can fix it.
With a few clicks of the mouse, you can set up WinSPC to generate reports at scheduled intervals that meet key Quality needs.
Careful consideration of some fundamental aspects of Statistical Process Control (SPC) can go a long way toward determining whether or not manufacturers are able to effectively prevent problems and control their production processes.
This is a crucial distinction that is frequently confused. Basically, specification limits have to do with the voice of the customer while control limits have to do with the voice of the process.
WinSPC can be set up to alert operators of production issues before defective product is turned out.
Certificates of Analysis help set the stage for success in manufacturing partnerships and reduce confusion.
There is a balance between automation, and feedback. If you totally remove the operators away from the feedback of periodic measurements, they may be less aware of the nuances of the process over time.
Operator ownership of production problems is necessary, but emails to supervisors about process changes allow you to get involved when appropriate.
We find that there are 3 common practices among companies who are effectively minimizing process variation. (1) Real-time monitoring of manufacturing with operator access to data. (2) Visualization of process output for operators and supervisors. (3) Investigation into problems and prioritization of improvement initiatives.
Total Productive Maintenance places shop floor workers in a position of responsibility, and stresses continually paying attention to what’s going on with the process.
SPC tells when to leave the process alone and when to react. By using SPC, companies can minimize the variation of their process by identifying, reacting to and eliminating extra sources of variation.
Production data can be captured for use from CMMs, ERP, and gages automatically by a computer system.
Inadequate measurement systems may result in inappropriate signals or even worse, charts that fail to detect important process changes. Thus, it is incumbent upon us to ensure that measurement systems are adequate for their intended use.
In order for an SPC program to succeed, line operators must accept and embrace the solution. Here are 6 steps to set yourself up for success across the team.
Quality managers around the country are leading initiatives to increase efficiency and lower costs. Where are you at on your Quality journey?
In WinSPC, sometimes you know what you are looking for, but you just aren’t sure where it’s at.
This is a crucial distinction that is frequently confused. Basically, specification limits have to do with the voice of the customer while control limits have to do with the voice of the process.
Nothing and everything. Though they are not directly linked, statistician and SPC expert Steven Wachs cautions that without evidence of process stability, capability data is useless.
Before applying statistical methods that assume normality, it is necessary to perform a normality test on the data.
It’s not subjective: Because it’s an objective measure of variation, standard deviation is an essential statistical tool for increasing quality.
Proper control chart selection is critical to realizing the benefits of Statistical Process Control.
The key is to specify a subgroup size so that significant shifts are detected with high probability and that insignificant shifts are unlikely to produce a signal.
We talk to companies everyday that are dealing with new challenges in Quality. In this video we will discuss common Quality issues and document the monetary value of SPC.
The subgroup size formula and application are discussed in the conclusion of this two-part topic.
Many believe that an out of control process produces defective parts. That’s not always true.
While the construction of control charts is relatively straightforward, often a more difficult question is: how do I know what process characteristics to control in the first place?
Highly effective SPC programs combine technical competencies, such as using the right chart and sample size for the application, with good management principles such as ensuring operator involvement.
An OC curve allows practitioners to determine a sample size that will result in the detection of those process changes that are of practical significance while minimizing the occurrence of false alarm.
Whatever your Quality objectives, sooner or later someone is going to ask for benchmarks on Quality performance. We offer a DMAIC-based approach to delivering these milestones and benchmarks. Central to this method is the implementation of a cost-saving real-time SPC system.
Blueprints can make data collection more intuitive to operators collecting data in WinSPC.
WinSPC dashboards organize and visualize Quality metrics. They can combine statistical summaries, event or activity details, and any of the 60-plus industry standard SPC charts.
When Statistical Process Control is applied properly, tremendous benefits in profitability and process understanding are achieved.
WinSPC offers intuitive Quality data entry and can capture independently from your CMMs, ERP and other sources.
A mold company that forms bumpers for major car manufacturers is painting the town red (and yellow and green).
By systematically detecting (and rectifying) sources of special cause variation upstream in the process, the important process outcomes become predictable.
Maybe the adage “if it’s not broken, don’t fix it” has given management an excuse not to change from old systems that do basic data entry and after-the-fact reporting.
Statistical Process Control is most effective when applied as close to the point of production as possible. Statistical Process Control charts have been called the Voice of the Process.
More companies are leveraging high speed vision systems to inspect multiple quality characteristics on their products.
In order to maximize profitability while complying with government regulations regarding net package contents, food manufacturers and packagers must achieve an optimal balance.
While enormous dollars are spent reacting to problems, Quality teams can excel to new heights by focusing on prevention: of product failures, of scrap, and of other inefficiencies.
An approach to deploying control charts with short production runs is to utilize charts of common characteristics across different products.
Characteristics with larger nominal values tend to have more variation than characteristics with smaller nominal values.
Looking just at the auto industry, GM has recalled roughly 3 million vehicles this year in the U.S. alone. In 2009, GM recalled roughly 2.2 million vehicles.
Real-Time SPC delivers efficiency and productivity gains by eliminating manual data collection efforts, but its real power lies in the ability promote continuous improvement and identify out-of-control process parameters.
Unfortunately, applying “simple” tools at the expense of tools with considerably more value (and really not much more complexity or difficulty) doesn’t cut it.
The purpose of control charting is to regularly monitor a process so that significant process changes may be detected.
You can use WinSPC’s trigger setup window to craft a corrective action message box with color significance and product-specific directives.
To provide executives and other leaders value, the data delivered to them has to be relevant and actionable.
Many manufacturing leaders believe that their production personnel use SPC properly, but the evidence suggests otherwise.
If you are trusting your process data to Excel, the time might be right for considering making the leap to an automated, real-time SPC solution.
WinSPC real-time statistical process control software can help you to easily generate a COA report to clear regulatory requirements.
Today, I’ll share some of the recent benchmark data that helps to put into perspective why a focus on improving quality with SPC makes sense for many organizations in today’s economic environment.
You can use filters in WinSPC real-time statistical process control software to zero in on the data you’re interested in and get help solving your critical Quality issues.
WinSPC reports can help you make a case for your Quality initiatives in statistical and financial terms.
An OC curve allows practitioners to determine a sample size that will result in the detection of those process changes that are of practical significance while minimizing the occurrence of false alarm.
Yes, you can chart deviation-from-target. You do this by creating a Target chart, a chart that plots the deviation of subgroup values from a target value.
As the bumper sticker says, “Shifts Happen” and so we generally want to use the slightly more liberal process capability of Cpk ≥ 1.33.
This article will review statistical hypothesis testing in general and then introduce equivalence testing and its application.
“Lean Manufacturing” (a.k.a. the Toyota Production System) is a toolbox of techniques to improve operational efficiency and eliminate waste.
Last month I began to answer this question by examining some of the 14 Principles of Lean Manufacturing according to Jeffery Liker. Let’s continue that examination.
Process Control is proactive rather than reactive. The key elements of process control are outlined in this article.
