“ Our objective is to improve production, not spend time producing or collecting data.”
−Senior manager of manufacturing innovation at a global electronics manufacturing leader
Today’s manufacturers face countless issues surrounding product quality and production in general, for example:
- Integrating data from disparate systems and isolated sources.
- Obtaining visibility into and understanding of multiple operational processes.
- The cost of poor quality goods, rework and scrap.
- Improving overall manufacturing yields.
A lack of visibility across operational processes hampers a manufacturer’s ability to react to changes in product quality and operational performance. Without this information, it’s dicult to make fact-based business decisions, leaving manufacturers to rely on employee intuition and guesswork. This can be very expensive if the decisions made are wrong or based on incomplete information. Downstream quality issues can also lead to significantly reduced customer satisfaction rates.
This is especially true when problems appear after the organization manufactures and sells the product. If companies can’t integrate both manufacturing and post sales quality data, they don’t know where problems are occurring or how to fix them.
- Disconnected view of enterprise quality. Disparate and isolated data sources limit a manufacturer’s ability to see quality issues across the entire operation. With a limited understanding of these processes, companies are often unable to solve underlying quality problems or make improvements.
- Failing to achieve yield and throughput goals.The inability to know when quality control problems arise harms yield and throughput goals. Without the ability to know when a failure will happen and how to prevent it, manufacturers must rely on human intervention, which drives down yield and throughput.
- Excessive scrap and rework Poor-quality goods that result in high rework and scrap costs can devastate a company’s bottom line. Without a clear understanding of quality eects on manufacturing and service costs, organizations can be left with a broken business model, unexpected expenses and reduced yields.
Manufacturers need to integrate data relevant to quality, productivity and utilization. They must also monitor the health of processes and drive sustainable quality and yield improvements – all while containing costs. Having the right tools and processes in place is essential for improving manufacturing quality in key areas, including asset performance and field quality.
We approach the problem by providing software and services to help you:
- Take advantage of the large volumes of data generated by the industrial Internet of Things (IoT).
- Support multiple data domains (including material movement tracking, genealogy data, process data and asset condition data), using a rich set of interactive root-cause analysis and quality improvement tools that can identify quality issues and operational performance degradations before they become serious problems.
- Gain process understanding across the entire manufacturing operation, employing best practice workflows and case-management capabilities to document findings and problem-resolution measures while promoting collaboration and knowledge sharing
About Pinnacle Solutions
Pinnacle Solutions, Inc. was founded to offer advanced statistical and analytic consulting services to collect, integrate, analyze and interpret the large volumes of data that organizations utilize to run their operations. From a concept to a complete implementation, Pinnacle Solutions’ team of data scientists help businesses understand the past, monitor the present, and predict future outcomes as they move the organization ahead. To learn more visit https://thepinnaclesolutions.com/.
Carrie Cristello 908-347-3157