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End User

Coca-Cola Beverages Africa (CCBA) is the eighth largest Coca-Cola bottling partner worldwide and the biggest on the African continent. CCBA serves 14 countries in sub-Saharan Africa, including South Africa, Eswatini, Ghana, Kenya, Ethiopia, Mozambique, Tanzania, Uganda, Namibia, Mayotte, Comoros, Botswana, Zambia, and Lesotho.

It boasts a diverse, pan-African footprint with more than 40 bottling plants with a capacity of 1.5 billion unit cases, serving over 600,000 outlets across the continent. CCBA employs more than 17,000 people and enjoys the number one market position for non-alcoholic ready-to-drink beverages in most of its 14 territories.

Systems Integrator

Advansys performs system integration services in the industrial automation, information systems, and project implementation spaces. They design and build control systems, integrate instrumentation, robots, controllers, PLCs, SCADAs, and people.

Problem/Opportunity

Downtime and speed loss on CCBA’s filling lines were captured manually by operators, into Excel spreadsheets at the end of each production shift.

This process led to the following challenges:

• Data loss - downtime events were not always captured

• Inaccurate data - operators could not capture their downtime durations accurately

• Manual capture was time-consuming, delaying decision-making and problem solving

• Inconsistent classification of downtime reasons and events

• Micro stoppages were impossible to capture manually due to the short intervals in which they occur

The manual data capture process produced inaccurate information. This made root cause analysis and decision-making difficult.

In addition, CCBA captured production volumes manually and there was inconsistency in the methods used. This required a systematic process and solution to support.

Solution

CCBA needed a solution to automatically capture and account for downtime, speed losses, and production numbers on all their filling lines. In addition, they required trustworthy information to support confident, timely, and accurate decision-making.

Requirements:

• A single source of truth, which presents information in an easy-to-digest format

• CCBA required the daily routines and processes to be identical across the group

• CCBA required a solution to standardize data capture, calculations and reporting across all countries and sites

• CCBA required a single platform from which business could retrieve and integrate data

The Flow Analytics Hub was selected as the central solution to automatically capture as much data as possible, transform that data into information, and become the single place where people and other systems access analytics-ready insights.

Signals from the filling lines were historized in a Canary Historian. These included the actual stop events and production counters on each line.

An information model was built in Flow, ensuring that every site and every line conformed to an abstracted naming standard for assets and KPIs. Data from the historian and other sources were connected to this Flow model. The data is now automatically and continuously transformed into up-to-date, actionable information.

Flow solved the immediate problem (manually captured “information” that could not be trusted) by automatically transforming signal data as events occurred with no manual steps. With Flow, downtime events are recorded based on the real-time state of the filling lines. Flow can account for every stop, including an exact duration. In addition, Flow will automatically categorize the stops, depending on their duration.

Flow then further aggregates and calculates KPIs for additional monitoring, for example, how efficiently the lines are running, how reliable the teams are against their expected shiftly or daily targets, etc.

Flow provides several mechanisms to integrate into other systems. For this project, Advansys chose to build a customized and integrated Inductive Automation Ignition front-end application to combine real-time data and the resultant Flow information, including manual categorization capability where required.

All this was achievable using the Flow API. Not only has Flow provided a single source of truth, but it has given CCBA confidence in its decision-making. The Flow information is presented to shop-floor operators and managers via Ignition and is also published to CCBA’s Data Warehousing tools, pre-calculated and analytics-ready!

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Results

17 sites have been transformed from manual entry to Flow automation using a standardized asset and KPI naming model across all sites. These 17 sites now trust their line performance information and constantly use their Flow reports and dashboards to make confident decisions.

Having a standard Flow model, including asset and KPI naming, has automated and simplified the ability to benchmark and compare across CCBA’s production sites.

Valuable information from Flow is then published to CCBA’s Data Warehousing solution in a contextualized and calculated state. We can’t wait to see how this capability transforms CCBA’s performance going forward.

Using a template-first implementation approach within Flow’s modeling, CCBA can ensure that all KPI calculations across multiple sites are standardized and locked down. This ensures that the implementation process adheres to governance policies and ensures that the resultant information is trustworthy.

The template-first approach has increased the speed of model iteration as changes to the templates are easily and rapidly rolled out to all sites. By adhering to a standard historian tag naming structure and building “auto-addressing” into the Flow asset and KPI templates, Advansys can implement this solution to a new packaging line within a few hours, thus reducing the time-to-value.

Project Info

Number of sites currently running Flow: 17

Number of sites still to be rolled out: 25

Number of sites after completion: 42

• South Africa: 13 sites

• Kenya: 6 sites

• Uganda: 3 sites

• Mozambique: 3 sites

• Zambia: 2 sites

• Ethiopia: 6 sites  

• Botswana: 1 site

• Ghana: 2 sites

• Islands: 2 sites

• Namibia: 2 sites

• Tanzania: 2 sites

After completion:

• 444 events across 148 lines

• 37 000 measures (KPIs) across 148 lines

• 900 reports / dashboards across the 42 sites

• More than 700 people across the 42 sites will be using Flow reports and dashboards daily

• Data Sources: Canary Historian, Microsoft SQL Databases

• Integration: Ignition, Data Warehouse solution

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