The data generated in the production processes is the most valuable asset of the production plants. Data becomes knowledge of the operation and is at the center of the analytics that allows making well-informed and actionable decisions.

Data must fulfill three criteria in order to be reliable: security, availability, and usability.

Security: Ensure the integrity of the data in its life cycle: reading, storage and exposure.
Availability: Maintain the indexing of large volumes of information to be delivered in a timely manner.
Usability: Guarantee the context of the data and mechanisms of exposure through state-of-the-art services

Why Big Data? Industry 4.0 projects enable manufacturing plants to generate new and more ways to capture data – not only limited to sensors. This includes digital forms, photos, videos, sounds, and more. Our Big Data solution enables flexible infrastructure architectures using cloud, data center or hybrid models.

Ibisa Space, our Big Data component allows companies to have unlimited storage for their new data asset.

Ibisa Analytics is the component to develop analytics reports.

What makes your smartphone truly valuable? More than 65% of the time we use our cell phones, it is to collaborate with others. Why? To make our life easier.

For us, the purpose of Industrial Digital Transformation is to improve the day-to-day operations at the workplace for people, reducing their non-value-adding activities and allowing them to be more efficient in their jobs:

– 40% reduction in non-value-adding activities

– Reducing downtime by more than 27%

The birth of Industry 4.0 comes from the concept of intelligent plants or SmartFactory, which is defined as intelligent and real-time collaboration between people, machines and processes. This is precisely this type of solution that Ibisa allows to develop.

ibisa Apperator is our mobile application that allows us to collaborate through functionalities of task management, notifications, chat and shared digital forms. This application becomes the driver to make life easier for operators, technicians, supervisors and to carry out daily tasks on the production floor

Manual and paper-based data collection is part of the day-to-day in many production processes. There is a great opportunity to improve these procedures through the use of digital forms with the kind of industry 4.0 technologies that ibisa delivers to its clients:

• 8 out of 10 production plants still collect control information on paper production and maintenance.
• A production plant has between 60 to 240 forms for manual completion.
• In 6 out of 10 times, lack of precision in production data is due to errors at manual data entry.
• An average plant worker can save an average of 42 minutes per day by automating the collection of information.

ibisa Forms allows you to design and publish new digital forms in minutes: Its great flexibility allows you to replace all existing forms in the production plant. Add functionality and control to digital forms by orchestrating their use through the workflow component we call: Ibisa Process.

ibisa Forms can be filled out from any web browser or Android and iOS mobile device, using our ibisa Apperator application. The application adds the following capabilities to digital forms:

• Offline use.
• Interactions with NFC tags and QR codes.
• Add photos, videos and voice notes within a form.
• Have contextual information and metadata about the completion of the forms (user, time, place).

The power of collaboration, IIoT and MOM (Manufacturing Operations Management) united in a single Industry 4.0 platform.

The benefits of incorporating a workflow engine to our digital platform are innumerable and make Ibisa a unique platform. Our main objective is to establish the digital transformation based on the ideas of those people who are the day-to-day operations.

Why incorporate workflows into your digital transformation program?

Innovation: Giving life to the best ideas! Ideas that come from the people who are in the operation every day. Our workflow engine is a perfect tool to translate these ideas into digital solutions: Design the interactions between people, machines and processes to achieve the business objective.

Context: Digital initiatives aim to take advantage of data for analytics, workflows enable the digitization of procedures. We help to frame and contextualize data in order to have high-context analytics that is congruent with the reality of daily operations.

Standardization: Each procedure is essentially a workflow. And production operations are governed by procedures. For companies that strive to teach procedures and to standardize their operations, ibisa Process allows procedures to come to life and be applied in accordance with business rules.

Integration: Workflows acquire valuable information from processes and with our integration connectors, they can deliver this information to other applications. ibisa Process is ideal for orchestrating information between multiple systems such as ERP, MRP, MES.

Give voice to machines and operational assets.

The industrial internet of things is revolutionizing the way of obtaining information from operational assets, be they sensors, machines, PLCs, control systems or SCADA. Driven by the benefits of having a secure, agile and efficient way to access process data.

ibisa Link Is our IIoT Gateway, with integration capabilities to any data source. Works wirelessly for easy installation anywhere in production.

ibisa Link also is an Edge Computing solution with powerful algorithms to compress real time data from and at the plant floor.

Data collection is the fundamental pillar of any initiative of industrial digital transformation (iDX). Through this layer we give a voice to the assets, creating a common language that allows communication and collaboration in the operation.

There are many possibilities to use Artificial Intelligence or AI in order to anticipate, predict, find patterns and much more. Our Ibisa Insights component is the engine in charge of running these algorithms developed in R or Python.

There are generally two types of models: classification and regression models. Depending on the objective of the algorithm, and the business question to be solved, one of these two models is selected.

Classification models: They are used to identify an event and classify it as a predecessor of a certain kind of future event. For example, if you want to know if a critical equipment is at risk of failure or downtime.

Regression models: These help to answer much more specific questions, applying regression analysis to patterns or situations from which the algorithm can learn continuously. For example, if you want to understand the medium time between failures.

Ibisa’s Artificial Intelligence solution is also a tool for creating virtual representations of equipment based on historical data statistics, also known as “Digital Twin”.

The uptime of critical assets such as machines, pumps, compressors, etc. is a determining factor for the productivity of the plant. Asset management must focus on objectives such as:

• Continuity of operation: Increase Reliability
• Optimize maintenance: Cost Control
• Extend the useful life of the asset: RoI over CAPEX
• Reduce the probability of failures and accidents: Industrial Safety
• Reduce CO2 footprint & Energy consumption: Energy Efficiency

With the power of Advanced Analytics, you achieve these objectives: Our Predictive Analytics models allow us to realize failure predictions and provide 6-12 months forecasts reliability levels. Thanks to Artificial Intelligence, these models are dynamic and continue to learn from the behavior of the asset, in order to continuously improve their predictions.
The ibisa platform enables an integrated End-to-End solution: The ibisa Link reads and processes all variables that are critical to asset operation. The ibisa Link has Edge Computing capacities, in order to deploy Advanced Analytics models on-premise.
In our ibisa Proactivity module we generate predictive models.
In ibisa Analytics, reports and dashboards are displayed to support decision-making in asset management.