Integrated IoT Solution for Process Optimization in Leading Publishing Firm

Project Overview

Modern printing and publishing houses integrate multiple machines for printing, binding, and packing. Our solution provides a kiosk-based view of the printing press—comprehensive and, at the same time, specific—by converging all the printing process and machine data on a single platform.

Client Profile

The client is a leading publisher of competitive exam guides in India. Five years ago, they branched out into academic book publishing and is now a strong contender in the market.

Business Requirement

The client has a state-of-the-art printing press with multiple machines. However, collating shop floor data remained a challenge. The client wanted an application that would facilitate shop floor data collection. The solution should further help improve operational efficiency by providing analytical insights.


We built a solution on our flagship IoT platform, SeeMyMachines, which captures data from all the machines and offers an integrated and intuitive view of the press.

Integrated, Real-Time View

The application we built provides a virtual view of the shop floor, which the client can access from anywhere. Each machine and its production status are visible on the app dashboard. On selecting a machine, print managers/supervisors can see a more detailed, live view of daily production status, machine speed, and the operator details.

Efficient WorkFlow

Our solution brought to an end the tedious paperwork in print job allocation. It interfaces with the ERP system to fetch planned jobs and pushes the job information to the respective kiosks on the shop floor. This information is picked up by the respective machine operators who then set the printing jobs in motion.

Continuous Performance Monitoring

The platform presents yearly aggregated data on machine utilization and downtime. Using historical operational data, the application calculates various machine performance parameters like Overall Equipment Effectiveness (OEE), availability, and quality. The efficiency of operators in each shift is monitored by analyzing parameters such as the number of pages printed, ink and paper utilized, and the amount of wastage. The data is displayed as intuitive charts for business users.

Sensor System for Predictive Maintenance

Machine condition is monitored continuously by means of sensors such as temperature and vibration monitors that are integrated with the machines. Our solution acts as a predictive maintenance tool for the printing press with the help of predictive models for machine failure built by utilizing historical machine data and machine learning algorithms. With this predictive maintenance system, our client is able to avoid unexpected machine breakdowns, plan maintenance, and reduce the cost of operations.

Ticketing System to Optimize Maintenance

The solution combines an asset management and trouble ticketing system to provide an efficient system for monitoring Service Level Agreements (SLA). Manuals, contracts, and other documents related to the machines are stored digitally and linked to the respective machines. This enables quick and efficient retrieval of documents related to the machines. All maintenance issues are logged and assigned to the right service provider on the platform for timely resolution.

Key Features

  • Integrated view of machines in the printing press
  • Individual machine view (status, counter, speed, job, shift)
  • Fast and real-time data analytics
  • Live status of machine performance
  • Real-time data on printing jobs (day counter)
  • Tracking of shifts and operator details
  • Predictive maintenance of machines
  • Tracking of KPIs such as OEE, availability, and quality
  • Monitoring of operator efficiency
  • Reports on jobs and shifts
  • Integrated asset management and trouble ticketing system
  • User-friendly web and kiosk-based view

Technologies Used

Play Scala Spark Kafka MongoDB Hadoop Node.js React Python

Business Benefits

  • The solution provides a unified view of all the machines in the printing press. It removed the manual effort that was required earlier for operational data collection.
  • Insightful decision-making became possible for business owners who can now track important KPIs such as OEE and machine availability.
  • Operational failure and adverse consequences were reduced through early detection of machine problems.
  • Machine maintenance became timely and efficient due to the integrated trouble-ticketing and asset management system.
  • The solution simplified contract management as well as the enforcement of Service Level Agreements.