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    Case Studies

April 2, 2021

Glass manufacturer optimizes production line with Makoro™

Glass manufacturer optimizes production line with Makoro™

This glass manufacturer has been using reports and analysis techniques for the last 10 years to understand its production data. They have been using a variety of data aggregation and statistical analysis tools for self-service analytics, building their own “screens” using their home-grown and vendor-supplied tools, and finally, rolling out these tools to their 4 locations globally. 

The manufacturer has an advanced data analysis infrastructure, which supports both mobile and desktop to enable easy access from anywhere. They typically monitor around 800 to 1000 data points in their lines across several processes. The current process looks like this:

  1. Aggregate data from OPC servers and data historians.
  2. Based on this data, process experts work with a set of tools to monitor the processes to make sure they are working optimally.
  3. A separate team of data experts uses this data to visualize, create and share reports and dashboards.
  4. At several points during this process, the data engineers transfer parts of the data to a cloud-based advanced analytics system for deeper analytics.
  5. If one location built a set of asset monitoring tools to send notifications based on asset conditions, they would then share the tools across locations. This “rollout” happens once in 6 months.
Business Challenge

At a recent virtual event, the manufacturer learned about Makoro™ and how they can potentially move away from rolling out tools to rolling out recommendations to their plant locations. Recommendations are giving them new ideas for improving their production operations. Moving away from making data and tools available to rolling out recommendations give them a faster return on investment as they can see the improvements each quarter, and they can spot the potential for further improvement. 

Transformation Story

With Makoro, they are gradually phasing out reports and dashboards as recommendations and insights are available in almost real-time. Most of the ad-hoc analysis and manual pushing data on demand to the cloud is being taken away as Makoro™ automates the analytics on the cloud and edge as required. Makoro™ makes the rollout process redundant as each location has access to recommendations based on their data, syncing up learning from these recommendations once each month. Lack of manual intervention in Makoro™ will allow them to monitor 500 additional data points on each of the main lines, and also extend monitoring to other auxiliary processes.


With the adoption of Makoro™, they are putting their data historians and OPC infrastructure on the back end of Makoro™ connectivity. They are able to leverage all the data they have been gathering over the last several years, but instead of using the suite of analysis tools, they are letting Makoro™ do all the heavy lifting in terms of analysis, analytics automation, and visualization. 

The end goal is to use Makoro™’s predictive recommendations to eliminate unplanned downtime and production outage completely.

April 14, 2020

Auto parts manufacturer optimizes equipment performance with Makoro™

Makoro™ in auto parts manufacturing
Business Challenge

Auto parts manufacturers want to continuously improve asset management programs for critical assets by reducing maintenance costs and improving the visibility of the maintenance process.

Business Story

This auto parts manufacturer has three manufacturing locations – Business Story each using an inventory system, a maintenance system, and two custom applications developed in-house with limited integration between them to manage the performance of manufacturing assets.

Manual interaction with these systems has resulted in process inconsistencies, higher costs, zero visibility and has constrained the company’s asset performance management program. Their maintenance expenditure has been increasing over the last three years, recently reaching 30% of the COGS.

This manufacturer wants to reduce maintenance costs and human errors in the maintenance process, improve visibility initially within a plant location and eventually across all locations.

Transformation Story

The manufacturer benefits from simple recommendations delivered by Makoro™ as well as from the Recommendations dashboard which tracks maintenance metrics and correlates it to recommendations.

The solution works like this:

  • Smart devices and sensors connect to Makoro™ Edge deployed on gateway devices. Gateways in turn connect to Makoro™ Hub to send machine and operations data, such as flow velocity, oil and water temperature, vibration readings, machine working hours, etc.
  • This data is then combined with data from enterprise applications and analyzed using a set of business rules and the predictive, Al-powered algorithms of Makoro™ Mind.
  • When Makoro™ identifies a potential problem, such as a blockage in a filter that requires the attention of an operations manager, it sends notifications and proactively creates maintenance requests, schedules and assigns the requests, and makes recommendations on duration and parts.
  • As users interact with the recommendations, Makoro™ learns and improves from the interaction patterns and over a period of time builds a system where asset maintenance decisions are data-driven, traceable and validated by the customer’s workforce.
  • In the future, the solution will possibly be extended to other locations and can potentially be put on auto-pilot based on reinforced learning capabilities in Makoro™ from this location.

Makoro™ Predictive Asset Performance Management solution continuously and automatically aggregates and correlates data from the manufacturer’s in-house applications, inventory and maintenance management systems and delivers recommendations to optimize the use of assets and workforce while reducing overall maintenance cost.

  • Eliminated complex cloud infrastructure provisioning
  • 10% Reduction in Maintenance Costs
  • Accelerated deployment by 8X compared to custom solutions
  • 100% Process Visibility
December 1, 2019

Textile Manufacturers optimize energy consumptions with Makoro™

Makoro™ AI in textile manufacturing
Business Challenge

This T&A manufacturer has been faced with long product lead time for fashion items, rising material and labor costs, short product cycles, and reduced profit margins. The advent of fast fashion has put demands on quick production and frequent changes in product orders.

Business Story

Plant-level daily MIS reports including production efficiency, actual production, specific energy consumption per kg of yarn, and waste percentage are manually inspected and decisions made based on them. Reports and dashboards from multiple systems make manual decision-making further complex and time-consuming.

The industrial ecosystem, global sustainable business trends, and the eco-aware-consumer-driven economy are putting pressure on the manufacturer to be more sustainable, innovative, and agile.

The manufacturer does not have sufficient internal resources capable of driving effective and agile digital transformation.

Transformation Story

The T&A manufacturer benefits from simple recommendations delivered by Makoro™ as well as from the built-in capabilities of Makoro™ Mind – the Al platform that powers Makoro™.

The solution works like this:

  •  Makoro™ collects and collates massive volumes of data generated from every system including sensors and servers, and multiple IT systems – the MES system, loT platform, and RFID middleware.
  • Makoro™ further integrates shop floor control with digital sewing machines – unifying data from sewing operators and the sewing machines. It analyzes this data in real-time to make recommendations on improving energy consumption and reducing scrap.
  • Makoro™ rapidly and automatically diagnoses common problems with machines and discovers the root cause within moments, such as the machine operating at faster than optimal speeds leading to frequent needle breaks. Shop floor managers are freed from monitoring machine conditions and spending time troubleshooting problems manually.
  • Makoro™ loT integration helps in identifying weaknesses in the production process, thereby reducing machine downtime. With reduced paperwork and automated data collection, Makoro™ delivers an optimal decision support system for ‘Apparel 4.0.
  • Makoro™ RFID integration further optimizes the Processing Workflow by using RFID tags on different fabric bundles that automatically reconfigure the settings on the sewing machines. This saves an incredible amount of time and effort.

Makoro™ monitors the overall production flow to detect the bottlenecks in the sewing line, increases the agility of the factory, and balances the production line in order to increase the overall productivity.

Makoro™’s recommendations further ensure a predictable production cycle while improving asset uptime, optimizing energy consumption, and reducing waste, thereby reducing costs for users.

Significant process efficiency improvements are achieved across the complete process – weaving, coating, thermosetting, printing, cutting, and final assembly, as well as effective use of skilled manpower.

  • 11% Waste Reduction
  • 5% Energy Savings based on real-time monitoring
  • Accelerated deployment by 8X compared to custom solutions
  • 8% Improvement in Order-to- Delivery times