Jeff Erwin, VP of manufacturing at G&J Pepsi-Cola Bottlers, has been helping to accelerate the digital transformation while aligning with the company’s goals and mission to improve its operational efficiency and meet customer requirements and regulatory compliance challenges by tracking and measuring performance. According to Erwin, “sustainability, operational efficiency and digital transformation in manufacturing are important to G&J Pepsi-Cola Bottlers. Erwin highlighted the importance of real-time data accuracy and visibility. People, technology, and data are very important for their journey.
The importance of employee ownership in driving cultural transformation and their acceptance of data-driven decision making within the organization was also emphasized. Data is a valuable asset, and having high-quality data that people can trust is critical because employees must see the value to drive their behavior. According to Mr. Erwin, “G&J Pepsi-Cola Bottlers treats their employees with dignity and respect in a culture that motivates them, has values and integrity.” Employees must see the value of technology and digital transformation. According to Erwin, “digital transformation is not just about technology, it’s about the people, and also the employee’s acceptance of the changes.”
About G&J Pepsi-Cola Bottlers
G&J Pepsi-Cola Bottlers is a 100-year-old privately held company with headquarters in Cincinnati, Ohio. G&J Pepsi-Cola Bottlers began its journey in 1925 when two women in Cincinnati, along with their partners, purchased the New York Mineral Water company. Shortly after, they renamed the business to the Grand Pop Bottling Company. A decade later, in 1935, they became a Pepsi-Cola Bottler, and the name G&J Pepsi-Cola Bottlers was officially adopted in 1955. G&J Pepsi-Cola Bottler markets, sells, produces, warehouses, vends, picks, and delivers orders in partnership with Pepsi-Cola. The company is a fourth generation privately held company. The company’s mission is to deliver competitive and sustainable operating results and returns to shareholders.
The company has 4 production plants in Lexington, KY, Winchester, KY, Columbus, OH and Franklin Furnace, OH. They also have Warehouse locations in Athens, OH, Hamilton, OH, Maysville, KY, Ripley, OH, Wilmington, OH, and Zanesville, OH.
Tracking Production Line Efficiency and Downtime
Mr. Erwin told us that the company supports community, sustainability, and provides products, solutions and services that exceed their customer’s needs by delivering high quality products to their consumers. The company is using technology to help simplify unproductive work processes to allow people to focus on their core responsibilities.
Mr. Erwin explained to us that the ability to track efficiency and downtime is critical to the process and their journey. It is important that the company track and measure production line performance in real time using data from their PLCs, machines, and other assets to track production line performance and to identify areas for improvement. The company had been tracking efficiency and downtime but manually and needed a way to improve visibility and the ability to analyze the cause easily.
TPM is a methodology aimed at increasing production efficiency by ensuring that every machine in a production process is always able to perform its required tasks. The three goals of TPM are zero unplanned failures, zero product defects, and zero accidents. “TPM helps drive employee ownership of machine conditions. It is an approach to equipment maintenance that aims to achieve perfect production with no breakdowns, no small stops, no defects, and no accidents. Some of the key measurements that are important to the company include MTBF (mean time between failures/stops), average uptime, MTTR (mean time to repair), and other real-time data and analysis information. MTBF and MTTR impact uptime and efficiency and are particularly important calculations for the company.
The Challenge – Eliminating Machine Stops
A minor stop for G&J Pepsi-Cola Bottlers is defined as being less than 10 minutes of downtime. Below are some interesting statistics that Mr. Erwin quoted about minor stops that challenge the CPG industry, in general. For example, most stops are minor stops, and an average production line stops 20,000 times per year. An average production line experiences 6.4 hours of downtime in a day due to minor stops. Best-in-Class minor stop performers have nine times fewer minor stops on their production lines over laggards. And Best-in-Class performers have only seven minutes of unidentified downtime in a day.
Erwin told us that it is important to look not only at machine stops and failures, but also at machine changeovers. These metrics are crucial in understanding, analyzing, and improving the efficiency and reliability of manufacturing equipment. Machine stops can be planned for changeovers for example, or unplanned for equipment failures. Both factors affect MTBF and MTTR metrics. Using the new technology, G&J Pepsi-Cola has real-time information on over 1000 production lines with 10,000-unit operations. Their production line runs over 20,000 steps per year with many different assets.
Reducing Downtime and Increasing Uptime
Erwin shared his personal experience implementing technology across multiple production sites in just three months that demonstrated the potential of digital transformation. To improve their intelligence they deployed Sage Clarity’s ABLE (Automated Bottleneck Learning Engine) – a cloud-based data collection accelerator that provides real-time root cause analysis for machine downtime; Epicor LEDS Reporting for real time insights, tracking and performance, and Sage Clarity’s One View for Enterprise analytics for production intelligence reporting and analytics in the Cloud, and PTC’s Kepware for connecting equipment including Rockwell Automation, Siemens and Mitsubishi PLCs.
Sage Clarity’s ABLE is a Data Collection Accelerator that models production lines, integrates IoT (Internet of Things) edge data into business systems, and provides root-cause analysis for downtime and production issues. ABLE can be used as a data pipeline for manufacturing analytics, a next-gen Andon system, and a middleware for IIoT (Industrial Internet of Things) data integration.
