"As an engineer, I have been using STATISTICA for over 15 years and it has provided me with a wide range of analytical capabilities...In one instance, I was able to model industrial aluminum alloys heat treating and reduce the furnace cycle time by 54%, saving energy and increasing productivity."
— Hélène Lagacé
Lean Six Sigma Master Black Belt
February 10, 2013
Enterprise Manufacturing Analytics
In manufacturing, analytics need to be fast and straightforward, integrated with your company’s data repositories, so that they can be applied on an ongoing basis for continuous process improvement. Companies using STATISTICA analytic solutions benefit from having all of the stages of analytics in one software platform. STATISTICA is personalized, delivering the workflows, reports, dashboards, etc., specific to the role and responsibility of each person.
Manufacturing today is a complicated business with many challenges:
- Globalization: Manufacturers have complex supply chains including numerous suppliers providing input to processes, and they are held to strict demands and schedules by their customers.
- New Product Introduction (NPI): Manufacturers need to streamline the introduction of new products, from R&D to full-scale production.
- Competition: Customers’ demands for initial and ongoing product quality are very high. If one manufacturer does not meet them, there are several competitors who are making promises that they will.
- Warranty Costs: Manufacturers are focused on reducing costs, including the overhead of warranty costs from repairs and replacements.
- Root Cause Analysis: Manufacturers need the traceability and tools to identify at which step in the chain defects were introduced.
Root Cause Analysis
Manufacturing processes can be complex. Often there are several process steps, assembly steps, and test steps. Various raw materials and subassemblies from an assortment of suppliers are brought together to deliver a finished product. Key questions are:
- What are the most important variables that impact product quality?
- Which ones should we measure and monitor?
- What are the defining characteristics of the manufacturing process that cause scrap and rework?
STATISTICA provides a suite of tools for root cause analysis, empowering engineers and other quality professionals with the capabilities for quickly identifying the few important factors from the many.
Using root cause analysis analytics in STATISTICA, manufacturers have uncovered process understanding that was previously not possible.
Opportunities for cost savings include:
- better investment by monitoring and control of the inputs and parameters that impact product quality along with less stringent oversight of inputs and parameters that do not impact product quality
- improved management of raw materials and suppliers by defining the monitoring of process inputs that are critical to finished product quality.
Once the critical few inputs impacting product quality are known, analytics in STATISTICA provide predictive models that characterize the processes. The predictive models make product quality predictions for various settings of the process, enabling ‘what if?’ scenarios to be performed by the engineering team to determine how the process behaves.
The next logical question is “What should the inputs be and how should our manufacturing processes be run to achieve the most cost effective and robust product quality outcomes?” STATISTICA provides structured tools and processes for engineers to perform process optimization. Engineers utilize their subject matter expertise to define which parameters are easy to change or expensive to change. Engineers are able to interact with and scrutinize these recommendations to assess predicted versus current process performance, including % beyond specifications and Cpk/Ppk, to estimate the cost savings and expected product quality improvements. Engineering user interfaces result in recommendations that are target optimal ranges for all of the critical variables, including raw materials or other inputs, that become the values for the limits for process monitoring.
Incorporate Multivariate Statistical Process Control
With Multivariate SPC methods, you can find anomalies in high-dimensional data that otherwise are not visible. When looking at each dimension by itself, many anomalies or manufacturing defects are hidden and missed. Incorporate Multivariate Statistical Process Control:
- in order to detect abnormalities (quality problems) across many parameters, when each individual measurement may be in control
- to identify outliers that would not be detected unless all variables are analyzed together
- to automatically generate multivariate alerts when a process is predicted to be “out of control” given the relationships across parameters
Root cause analysis and process optimization define the most critical parameters driving product quality outcomes and what settings should be used to achieve repeatable and robust product quality outcomes, even with the expected variability in the other aspects of the manufacturing processes. These results feed directly into process monitoring, providing the definition of what to monitor and what values to apply as warning and control limits.
Unique in the STATISTICA approach to statistical process control are at least three major factors:
- What parameters to monitor? Which limits to apply to achieve the maximal benefit from monitoring? Many companies struggle with what to monitor and what limits to apply. STATISTICA provides a structured approach to employ analytics to provide the answers to these important questions.
- Model-based SPC provides ongoing, proactive predictions for product quality outcomes. Utilize models for how the processes should run to make ongoing predictions about the expected outcomes of current runs. An advantage is that this approach takes into consideration the interactions between parameters and provides a very sensitive, holistic assessment of the manufacturing processes at all times, with proactive alerts.
- Color-coded, Web-based dashboard summaries. STATISTICA makes monitoring easy with personalized sets of color-coded dashboard summaries with integrated drill-down. Managers and engineers enjoy a “plant view” of the manufacturing processes for quick and easy awareness of the status across the plant at any time, day or night.
Supplier Quality Monitoring
Most manufacturers have a complex supply chain including numerous suppliers. Monitoring the operations and quality of suppliers is a common problem. With STATISTICA, Supplier Quality Monitoring enables immediate insight into how your company’s suppliers are doing by:
- empowering suppliers with the tools and schedule to upload data for ongoing monitoring, aggregating and centralizing the data to trend suppliers’ data by part.
- allowing the configuration of the materials and parts and specifications for each supplier.
- automating ongoing supplier reviews with a focus on the suppliers and parts where attention is most warranted.
Manufacturing processes in many areas (including for example automotive, heavy equipment
, and semiconductor
manufacturing) involve a complex sequence of unit operations, with interactions between upstream and downstream processing, raw materials, media, and instrumentation.
Those manufacturing processes require that the quality assurance professionals and managers have access to the Hierarchical Process Cube
that contains all information about how the material moved through the sequence of steps, so that meaningful monitoring, qc-charting
, reporting, and root cause
and other analyses can be performed.
For example, process engineers need to be able to enter batch numbers for any process step (unit operation), and retrieve the relevant data properly aligned and aggregated over all other steps.
In STATISTICA Enterprise
, engineers and analysts are empowered to select the relevant process and easily gain access to the necessary data and to review the movement of materials and batches through the production process.
In STATISTICA, manufacturers configure secure, limited access to the latest status reports for their customers. Allow your customers to have Web-based secure access to review reports so they can self-service. Differentiate from your competitors by delivering transparency into your manufacturing operations. Save costs by automating these reports rather than reacting to customer requests for data and status reports. Customers may be external customers or internal stakeholders from processes later in your company’s supply chain.
Data Entry and Management
The STATISTICA platform includes data entry, providing complete flexibility in defining the data entry scenarios for each cell or unit operation. Easy-to-use Web-based data entry forms are configured specific to each data entry scenario. The data are stored in a standard relational database, completely integrated with the analytic capabilities and reports of the STATISTICA platform.
Configure, publish, and monitor Web-based dashboards of key performance indicators. Deliver relevant information directly to the stakeholders, everyone from the shop floor to management.
STATISTICA Dashboards are completely configurable. Examples include summaries of throughput metrics, tracking of rework and scrap, Cpk/Ppk summaries, and pareto charts of defects.