Increasing production with less capital

With operation performance unknown, forecasting the ability to meet increased market demand was ineffective. Building another plant seemed unavoidable, but the task would be time-consuming and expensive.

By Richard Phillips December 5, 2022
Courtesy: Polytron

 

Learning Objectives

  • A beverage manufacturer looked to improve production, but needed insights on from a digital data platform to help put together actionable insights.
  • Digital data capture enabled accurate and up-to-date production data across management and all shifts for decision clarity.
  • This ultimately saved the company money by delaying production of a new facility because they were able to get better efficiency from the current one.

System integration insights

  • Gathering data about a facility’s operations enabled a beverage manufacturer to understand what was really at the heart of their issues in the facility.
  • The beverage manufacturer gathered the data hidden in the aging machines to help create a comprehensive picture of what did and didn’t work.
  • They digitized their data and asset production, which helped the company streamline and automate their processes and save the company money by delaying production of a new facility.

When a beverage manufacturer was under pressure to meet growing market demand without increasing expenses, the company knew they needed to find the true problems and act fast.

Unfortunately, the manufacturer’s bottling lines were operating beneath peak efficiency, and aging line assets were creating excessive downtime and waste – or so they thought. The bottler’s leadership didn’t know how well their operations were performing and couldn’t effectively forecast their ability to meet increasing demand.

They knew they would need to build another plant. Construction would cost $50 million and take 18 to 24 months, slowing progress toward meeting market demand.

Unknown performance of manufacturing operations, OEE

The vice president of information services knew he could not provide the data the executive team needed to help facilitate their decisions. Manually-reported overall equipment effectiveness (OEE) was inaccurate and lacked data necessary to determine true utilization. Another issue of underperforming assets was the extra staff that had to be hired to firefight issues. The VP needed to better support maintenance and engineering with increased efficiency.

Finding the true problems required getting machine data

The VP and his team did not know how to get more out of the existing assets, how much improvement they could realize, or how to start. They challenged themselves to get more output from the lines already in use, while extending service life. To do so, they needed data hidden in the machines to point them to the most effective action.

The paper-based operator records provided no real-time, actionable insights to take corrective action for improvement. For a smarter company future, the upgrades had to begin in this plant and be replicated at scale in future plants.

Solution architecture, implementation provider, machine communications

The beverage manufacturer needed a solution that could help them assess the current state, envision a future state, then develop and deploy the technology to transport them there.

The VP began a search for a provider that could help them talk with their machines and get the insights they needed. They chose a system integrator to act as a consultant and solution provider for solution architecture and implementation.

Assessment of core issues: Automation, integration

Out of the gate, an assessment helped identify the core issues for the project related to a lack of real-time data, insight and communication:

  1. Manual recording of data was unreliable, not always accurate and time-consuming

  2. Real-time actionable information was not always available

  3. Rest of the organization lacked visibility into how manufacturing was performing

  4. Lack of integration between the various data silos.

Outlining six automation goals to achieve desired manufacturing results

To deliver the desired results as efficiently and effectively as possible, the integrator team implemented a balanced approach of automatic data collection from most of the machine programmable logic controllers (PLCs) and smart Industrial Internet of Things (IIoT) devices in areas where PLCs did not exist. Using the technology platform in conjunction with the smart IIoT devices, The integrator sought to:

  1. Increase production throughput

  2. Provide real-time actionable information to drive manufacturing improvements

  3. Provide manufacturing visibility throughout the organization

  4. Provide a platform for digital transformation that supports enterprise growth

  5. Integrate data from multiple systems to provide a single version of the truth

  6. Migrate legacy data silo applications into the new platform.

Accomplishing these goals delivers real-time data and feedback with a minimal footprint, no production disruption, and no need for updates to connectivity or other infrastructure.

Overview dashboards are displayed on large monitors throughout the plant and in offices. Teams can quickly identify the status of each production line in the plant. Courtesy: Polytron

Overview dashboards are displayed on large monitors throughout the plant and in offices. Teams can quickly identify the status of each production line in the plant. Courtesy: Polytron

Solution phases delivered ROI

The implemented technology served as a digital platform that helped integrate, aggregate, contextualize, display and report actionable insights. Multiple solutions were implemented using this Digital platform over a four-year period. Each phase delivered a return on investment (ROI) that helped fuel the subsequent phase. Phases included the following:

  1. Performance management for three filling lines with automatic data collection from more than 10 PLCs and using standard user interfaces, dashboards, and reports. Several PLCs were upgraded to have EtherNet/IP capability. The PLC system tracking file captured machine state, production/reject counts and the first fault for each machine.

  2. Enterprise resource planning (ERP) Integration for downloading production schedules automatically.

  3. IIoT smart devices implemented in empty bottle area to count bottles where no PLC existed.

  4. Performance management for Line 4 and extension of data collection to additional machines.

  5. Historian for process and packaging time-based data analysis.

  6. Maintenance management implemented to replace a legacy point solution that acted in a siloed fashion, was unintuitive and had grown obsolete.

  7. Rollout to the second factory with all the functionality listed above.

  8. Scoreboards across many machine centers for real-time shift performance.

  9. Quality management implemented to replace a legacy point solution that did not support most of the quality forms required.

  10. Rollout to the third factory with all the functionality listed above.

  11. Multi-plant visibility of performance, scheduling, maintenance and quality.

Developing a solution: Data capture supports manufacturing decisions

To meet the increasing market demand, these solution phases guided the manufacturer to their goal. Upgraded digital data capturing allowed for real-time, accurate production data to support decision clarity. In just three months, the performance covered the cost of the project, delaying the need for new plant construction and successfully exceeding the company’s goals.

The beverage manufacturer evaluated using the platform for warehouse management, quality management with SPC, finite scheduling, visual workflow and expanding the technology to all the manufacturing assets in both facilities.

The project enabled the manufacturer because the platform would grow with them and allow for expansion into other functional areas and multi-site deployments.

Automated data capture project results: 6-month ROI, phase 1

Digital data capture eliminated the inefficient paper-based records and workflows, and it enabled accurate and up-to-date production data across management and all shifts for decision clarity. The digital solution was a small investment compared to a new line – or even a new plant. With the accurate data presented to the organization, the manufacturer realized a significant improvement in their line performance.

  • Measurable ROI across all phases including 6-month payback on Phase 1

  • Out-of-the-box user interface screens, dashboards, and reports available on tablets, large production monitors, office computers, and mobile devices

  • Increased output at factory one, enabled construction of the second factory to be postponed by 18 months

  • Platform for rapid and cost-effective deployment of any new requirements.

Updates: Pallet tracking, quality, predictive scheduling

Today, the beverage manufacturer continues to leverage the digital platform for functionality as the business needs change. New functionality has included:

  • Tracking of pallets going into warehouse and reconciling with ERP.

  • Salesforce integration to automatically capture customer complaints into a quality management system (QMS).

Additional functionality is being considered based on the business’ priorities which includes:

  • Predictive scheduling to optimize production even further by considering order delivery commitments, changeover times, ingredient availability, asset/resource availability, etc.

  • Visual workflow to allow everyone to understand status of each process, next step, etc.

  • Supply chain integration to gain greater visibility into materials flowing into factory and product leaving the factory.

Seeing this vision become a reality over the past four years demonstrated that if a small manufacturer can benefit from this type of solution, then the impact and ROI for larger manufacturers should be even greater.

Richard Phillips, PE, PMP, is director of smart manufacturing, Polytron Inc. Edited by Chris Vavra, web content manager, CFE Media and Technology, cvavra@cfemedia.com.

MORE ANSWERS

Keywords: automated data collection, solution architecture, overall equipment effectiveness (OEE)

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Original content can be found at Control Engineering.


Author Bio: Richard Phillips, PE, PMP, is director of smart manufacturing, Polytron Inc.