Solutions

Shift handover solution

Having a proper shift handover solution is a basic element to control and optimize the operations of any business. Our solution was created to easily adapt to any kind of business, operation and working methodologies. It has a very user-friendly interface with a minimal adaptation and learning time.

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Harmonize your shift handover with our solution

Our shift handover solution is centred around providing a flexible and fully configurable web-based platform that allows any kind of business to successfully record and transition working shifts data.

By digitalizing the shift handover process, we enable and strengthen following assets:

IMPROVEMENT OF YOUR DATA

The accuracy of your shift data is instantly improved.

HIGHLY FLEXIBLE

Everything is easily configurable.

INTERFACE WITH EXTERNAL SYSTEMS

Reports can be directly submitted to external systems.

WEB BASED TOOL

Our solution works in any kind of web based environment.

Process simulation

AG Solution provides a complete offline process simulation. The behaviour of this offline process will be the same. This allows you to improve testing and training, to limit your start-up time and to even limit downtime of an existing installation. This simulation is used to perform FAT test upfront and to train operators in an offline simulation environment before going to the plant in real life.

Several scenarios are worked out to simulate different situations in the test environments. These scenarios are situations that can occur in the real production environment. This set-up is done in the operator training to work out possible solutions.

This process simulation has the possibility to create a digital twin.  Together with our data scientist and IT professionals, we run simulations before the psychical installation is even build. The digital twin makes it possible to run several tests before going live. An excellent tool to build these digital twins is SIMIT from Siemens.

OEE (Overall Equipment Effectiveness)

Overall Equipment Effectiveness, better known as OEE, detects the percentage of your planned production that is effective/productive. Defining your OEE is a very well-known method in the process industry.

It is calculated by many, but rarely in an automated way and in real-time due to a low digital maturity.

Assisting in the development of your digital maturity is at the heart of AG Solution. We have many success stories of implementing and improving OEE reporting systems. An automated and real-time OEE will easily and rapidly indicate the bottlenecks of your process ensuring the ROI. 

Predictive process monitoring

Predicting a certain process allows you to actually predict the future. AG Solution provides you with the necessary tools to find out when for example a failure, blockage or production stop can occur.

Our algorithms provide the insight into the expected lifetime of a certain asset. Based on your historical data we provide a specified window where we predict the likelihood of the asset breaking down. With this knowledge it is possible to do early maintenance or prolong it.

Predictive maintenance

AG Solution applies data-driven models based on variables that detect your machine status and health in order to predict the next maintenance window. Excels that show you when to go into maintenance are a thing of the past.

MAINTENANCE BASED
ON DATA
PREVENTION FROM
DOWNTIME EVENTS
SET AND FORGET
MODEL

One of the benefits of having a modelled system by AG Solution is that you only have to go into maintenance when needed, based on data, not scheduling. Our expertise together with your process knowledge prevents downtime events like faults or breaking when your machines should be running on a schedule. The model is set and forget, allowing it to auto-update that learns from the past and adjusts accordingly.

Causality Mapping

Having performance monitoring as data streams in the system is a good step towards maintenance and monitoring of your system uptime. In practice, having these streams enables and empowers you to analyse which event happened first.

Analyse the causality of downtime events:
For this instance, downtime events of server clusters were analysed to investigate multiple root causes, causing overloads to the server resource consumption (Ram/Cpu) where effects of this would cause network failure in the system. Knowing the variables and event streams, an analysis is applied to analyse the correlation of events in order to find the root cause of the problem.

  1. Predict and prevent the causes of downtime events
  2. Effectively monitor and jump into downtime events
  3. All blockages or stops can be detected early on.

Route management control

Route management control can be described as an internal GPS system for your most complex simultaneous material transfers.

It is often used in very complex bulk silo or tank park installations. This control management considers following factors which determine the possible routes to move products from one source to another destination:

  1. Availability of equipment
  2. Product validation
  3. Energy consumption
  4. Efficiency
  5. Contamination of product
  6. Quality control of product
  7. Customs clearance to deliver product to customers
  8. Track and trace system for all transfers
  9. Reporting of transferred quantities

Libraries standardization

We adapt the library to the functional needs of your business. It is a fundamental, well tested environment to guarantee a safe, well structured, maintainable and uniform software development. The library will bring a standard in your automation as well as at developmental and operational level.

  1. Improve the quality of your system
  2. Less dependant on who is programming
  3. Easy cooperation with different integrators
  4. Better maintenance and governance of these libraries

We support our customers in the creation and maintenance at the level of:

  1. Siemens PCS
  2. TIA portal
  3. Siemens S7

Process optimisation

Process optimisation at AG Solution can be done using algorithms that analyse the process parameters and give some predictive capacities. Given historical data, a model can ‘learn’ and predict a set of variables controlled by the operator (for example, the production rate). By using the predictive power of machine learning models, we make it possible for the operator to test the results of his actions in real-time before the process happens.

This allows the operator to test different actions before applying them to the real process, and to steer the outcome of the process. The optimisation module will provide actionable output. For example, giving the operators advice on which variables they should adjust to maximize production, as shown in the picture below.

Together with AG Solution you will be able to optimize your overall process. We will build machine learning (ML) algorithms and we will detect the controllable variables so that the model can be trained in order to get the optimal configuration of your working unit.

Virtualization

There are many advantages when using virtualization in plant environments. Our virtualization solution allows you to separate and distribute critical applications and data centers in a safe way.  By applying our solution to your plant, the cost of the HW Infrastructure, maintenance and administration will be reduced making your ROI increase.

As our system can be used to test scenarios without affecting production in isolated environments, the plant downtimes are shortened in:

  1. System upgrades
  2. Application deployments
  3. Implementations
  4. Migrations
  5. Lifecycles

Virtual Sensors

AG Solution applies machine learning techniques and strategies to create virtual sensors that are data driven. These sensors have no downtime and allow to prediction upcoming values. They are reliable when it comes to failing sensors or inaccurate  sample points.

For example: In a corrosive line, a pH sensor for measuring acidity does not last long. It degrades over time, and with it, its measurements are less and less accurate. The strain on maintenance to constantly configure, calibrate and replace the sensor is costly. Having a robust data solution, based on taken samples, product data and in-line measurements of the influenced pH. Based on years of data, a modelled solution is engineered, predicting the pH of the stream in a real-time manner, based on the input data. The modelling and execution of the model are done on-site in a machine learning node, allowing interactions and finetuning as well as re-modelling and retraining.

Golden Batch

Our Golden Batch solution enables our customers to record the perfect time-based profile for all process values that influence the product quality. Thus describing the perfect =golden batch of product mathematically and visually. Next, our solution monitors your real-time process parameters, comparing them to the golden batch. This allows our customers to correct and “save” their batches.

Golden batch (often also called the Golden profile) is defined as the time-based profile of the process values that were recorded for a batch with the best product quality targets. Nowadays, continuous process verification is crucial to reach manufacturing excellence. The real-time verification of critical process parameters is crucial to reduce the unforeseen results for your batched production. Golden batch enables this capacity and  allows the study of the unexpected results, detecting process variability and sets a clear pace for continuous improvement.

AG Solution’s expertise is to utilise knowledge from a wide-range of process experience to work together with your continuous improvement department and create a living solution to reproduce your best batch.