How do you know you have a quality problem, or more importantly, when? Is it when product is returned from suppliers? When you receive complaints from your customers? Or worse, is it when you’re facing a recall? Many manufacturers lack true visibility into and across their shop floor and it’s costing them unnecessary time and money.
- Lack of real-time information leads to a “fire fighter” approach to resolving issues
- Home-grown or paper-based checks and reports are time-consuming and make it difficult to share results in a timely fashion
- Management lacks key information needed to make decisions
Blueprint: The first step
Deploying a Manufacturing Intelligence software solution across your shop floor will increase plant visibility by enabling you to quickly and easily capture and analyze data in real-time. As a result, small issues can be pinpointed and fixed before they turn into larger, more costly problems. Being able to collect, unify and report on data across all of your lines helps fill out the complete plant picture.
Real Problems, Real Results
Gained Total Quality Management with “Best of Breed” Methodology
SanDisk, a manufacturer of flash memory cards and components for consumer electronics, already had both factory Manufacturing Execution (MES) and Quality Management Systems (QMS) in place, but neither provided the granular, real-time process data at the shop floor level needed to ensure quality consistency throughout production. Utilizing a “best of breed” methodology, SanDisk chose InfinityQS ProFicient software to integrate with their existing system infrastructure, rather than spend months customizing their MES system to do something that it was never originally designed to do. SanDisk’s quality and process control team gained a closed-loop solution that can place a hold on a lot through the MES, send notifications and alerts, and create quality incidents via QMS. SanDisk was also able to consolidate and standardize live production data for analysis and control. Ultimately this allowed the SanDisk team to act on every potential incident preventing the manufacture of defective products resulting in a significant cost savings.
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Ben & Jerry's | Secondary Challenges: Incomplete Plant View; Delayed Improvement Cycles
Pulls Reports in Seconds Instead of Hours
As a producer of super-premium ice cream, Ben & Jerry’s focus on consistently high product quality was hampered by slow, inflexible and costly manual and paper-based systems for collecting and analyzing quality data. To achieve their goal of streamlining quality control procedures to better identify cost-saving opportunities and ensure the highest levels of customer satisfaction, Ben & Jerry’s implemented InfinityQS ProFicient software. This enabled Ben & Jerry’s to automate data collection, integrate with terminals on the production floor and track variability in real-time across every production line. Reporting and analysis now takes seconds instead of hours, resulting in dramatically reduced paper usage, and enables the quality team and operators to fine tune processes with more precise specification limits. The result is improved run capability, raw material cost savings and a more consistent, higher quality product for the customer.
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Schiff Nutrition International | Secondary Challenge: Overwhelmed Shop Floor
Ease of Use and Reduced Scrap Rates
Schiff Nutrition is a leading nutritional supplement company with a portfolio of well-known brands. Schiff's previous quality control system was difficult to use, required ongoing customization that hindered real-time response to adverse events, and required costly proprietary hardware. By switching to InfinityQS ProFicient, Schiff gained daily operational benefits for the shop floor and quality team, including immediate insights into the entire production process. With no IT support required for the installation, start-up, or day-to-day use, ProFicient helped the company better understand its processes and reduce scrap generation on a real-time basis. Analysis of the collected data enabled Schiff’s management to identify which product and equipment combinations would produce the best product with minimal scrap rates.
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