Finding manufacturing visibility beyond the cables

Case study: General Cable saves in raw material use by decreasing inconsistencies in process variation across sites with a statistical process control (SPC) analysis engine; return on investment (ROI) is less than six months.

11/12/2014


General Cable approached InfinityQS International Inc. about implementing ProFicient, powered by a central statistical process control (SPC) analysis engine. InfinityQS implemented ProFicient at 14 of General Cable’s manufacturing locations in a terminalFor companies with large, global manufacturing bases, maintaining consistent processes from site to site is a challenge without complete visibility; a statistical process control (SPC) has improved quality and decreased waste across multiple sites globally for General Cable, after the Fortune 500 Company sought to improve its ability to control process variation and ensure enterprise quality from one plant to the next. Return on investment (ROI) is typically less than six months.

With annual revenues of more than $6 billion, General Cable (NYSE: BGC) is a global developer, manufacturer, designer, and distributor of aluminum, copper, and fiber-optic wire and cable products and systems, with more than 50 manufacturing facilities. Markets include energy, construction, industrial, specialty, and communications. Its headquarters location is Highland Heights, Ky.

As the company grew and acquired more product brands, it recognized the need for greater consistency in production data analytics across sites, to improve the ability to control process variation from plant to plant and create a standard approach to data collection and analysis. As a result, the company could ensure maximum quality, control raw material usage, and prevent operational inefficiencies associated with rework, giveaway, production delays, or customer complaints. 

Manufacturing intelligence, supply chain visibility

General Cable approached a provider of software for manufacturing intelligence and enterprise quality, about implementing software that uses a centralized statistical process control (SPC) analysis engine. The resulting solution addressed the needs of General Cable's supply chain, while increasing visibility and production consistency.

The solution was implemented at 14 of General Cable's manufacturing locations in a terminal server environment, including more than 100 applications to collect critical-to-quality data to control variations, monitor manufacturing processes, and ensure product quality. General Cable also integrated devices such as micrometers, microscopes, scales, and cameras.

Using the software, General Cable manually or automatically collects data points to produce flow charts and control charts. Plant floor operators use SPC to assist with machine control adjustments, while the quality team analyzes data to help identify areas for improvement. Meanwhile, all data is brought into a central repository for seamless analysis and a holistic view of General Cable's various sites' processes. The implementation is "creating visibility across our global manufacturing base and elevating the level of trust in the data," said Zack Tran, project manager, General Cable. "This work helps us identify opportunities, improve process variations, and control raw material usage, as we continue to uphold General Cable's commitment to produce quality products." 

Results, benefits, ROI

General Cable typically sees ROI on each individual plant implementation of the software in less than six months. But over the course of one year, General Cable specifically focused on using ProFicient for data collection and analysis on production lines in two manufacturing plants-a copper line in a Texas plant and two lines in an Indiana plant, one copper and one aluminum. This project was intended to identify ways to reduce process variation and improve raw material use, while maintaining or improving product quality.

Using the SPC software, General Cable:

  • Saw significant savings in raw material usage within one year on three production lines.
  • Used control charts to identify trends and increased Cpks (a process capability measure for statistical process control) to Six Sigma quality levels.
  • Eliminated duplicate data entry, drove out variations, and retargeted raw material usage.

Martyn Gill is general manager of Europe, InfinityQS International Inc. Courtesy: InfinityQS International Inc.General Cable continues to implement the software in more plants to increase visibility across its global manufacturing base.

Tran concluded, "The key to successfully implementing SPC is not only making sure data are collected frequently—a single data point isn't meaningful—but also knowing what to do with the data after they are collected." Using control charts in the software, "we can clearly identify trends in our processes and make adjustments accordingly. In one case, our actions resulted in significant increases in process capabilities, and that makes me very happy. If a process is capable, it improves product quality and saves money on all fronts."

- Martyn Gill is general manager of Europe, InfinityQS International Inc.; edited by Mark T. Hoske, content manager, CFE Media, Control Engineering, mhoske@cfemedia.com.

Key concepts

  • Manufacturing process visibility
  • General Cable saves in raw material use by decreasing inconsistencies in process variation across sites.
  • Statistical process control (SPC) analysis engine provides return on investment (ROI) in less than six months.

Consider this

With greater push for big data analysis, are you using statistical process control tools to create actionable information from data already at hand?

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