Predictive AI

What is predictive AI used for in companies?

Predictive AI is one of the most useful tools for leveraging business data to make decisions. But what is the reason for this prevalence, and how does it differ from traditional predictions?

The main reason is that it provides a roadmap for planning critical aspects such as sales and stock management, basing decisions on data rather than merely on individual experience or biased perspective.

It does not mean that the prediction results are unquestionable. On the contrary, the results become an additional tool that decision-makers can use to work more reliably, securely, and conveniently. In other words, human elements like experience and intuition are still necessary for making decisions with a higher success rate.

A key reason for AI and human experience to continue working together in decision-making is that each considers different elements of the environment. It makes them complementary, and ignoring either can lead to an incomplete view and less accurate decisions.

How does predictive AI work?

Before answering this question, it’s important to mention that before AI gained popularity, statistical models were used to plan sales, manage stock, etc. These models were the only data-based resource that allowed decision-makers to make informed decisions.

Today, AI combines statistical analysis with machine learning models. Machine learning mimics how humans learn, enabling AI to perform tasks like data classification and predicting future outcomes.

Machine learning is the set of algorithms that allows AI to learn from data. The accuracy of the prediction depends on factors like the quality and quantity of the data.

How does data quality affect the results of predictive AI?

To understand the impact of data quality on results, we could compare it to the learning of a student who reads books with outdated information versus a student who has access to updated information. The former is more likely to give incorrect answers on an exam, while the latter has a higher chance of success.

We can think of predictive AI as a student learning how the data in your company behaves and developing the ability to analyze it and make predictions. Continuing with the example, the more time the student spends learning, the better their results will be in exams.

In other words, learning is a skill that can be trained and has the potential to improve with the necessary resources for training. These resources are primarily high-quality data and time. Depending on the volume of data or the complexity of the prediction, training may require more time.

Another important aspect is having the right data for each prediction. For example, if we want to know the average ticket value for a customer profile, we need data that defines that profile, such as age, gender, or location.

In conclusion, predictive AI provides companies with tools to make data-driven decisions with a deeper level of analysis. However, the accuracy of the results still depends on human responsibility, such as the data provided and its quality.

At RCM Software, we work to ensure that companies can benefit from AI throughout the entire data lifecycle. That’s why our data orchestration platform and BI both feature integrated AI.

TEKNOSERVICE

TEKNOSERVICE: New Partner of RCM Software

TEKNOSERVICE, a leading Spanish hardware manufacturer, has recently joined the network of partners of RCM Software. We are very pleased to share this news with our community because TEKNOSERVICE possesses two characteristics that define our partners very well:

  1. Providing excellent service to their clients
  2. Constant innovation in their products and services.

The leadership of TEKNOSERVICE has enabled it to achieve various objectives, among which we highlight:

The only Spanish company approved by CERN

In 2013, it became the only Spanish company approved to provide computer services for CERN, the European Organization for Nuclear Research. In 2017, they renewed their relationship with CERN by implementing TTL servers for their computing center.

TEKNOSERVICE has managed to maintain this milestone by continuing to supply cabinets and storage equipment to Switzerland. Currently, it has prominent clients such as:

  • All regional governments
  • Provincial councils
  • Universities
  • Study centers
  • 2,000 municipalities

Own operating system: TLL OS

Another notable achievement of TEKNOSERVICE is the creation of its operating system, called TLL OS, which, thanks to its great flexibility and security, adapts to the needs of each company regardless of the sector to which it belongs.

Advantages of the alliance

The great potential represented by the combination of the credentials that attest to TEKNOSERVICE’s experience and quality, combined with the technological innovations we work on at RCM Software to offer increasingly competitive tools and solutions, allows us to be confident in the satisfactory results we will see in the future.

With this addition to the network of partners of RCM Software, TEKNOSERVICE’s clients will be able to enjoy all the benefits of the products developed by RCM Software in all their projects related to business intelligence, data analytics, data orchestration, artificial intelligence, data virtualization, and other related topics.

Benefits of AI for companies

What are the benefits of AI for companies?

AI (Artificial intelligence) offers many benefits in terms of optimization of processes of automation and digitalization for companies. If you want to know more about AI works and learn how to leverage the power of AI in your business processes, keep reading.

Improve the relationship with your customers.

The relationship with customers is a central matter for any company, as improving it you improve the overall business. That’s why companies use AI (Artificial Intelligence) to enhance their efforts in building stronger customer relationships. But how can it help? Undoubtedly, the starting point is its ability to help you understand your customers better. It is where AI can be helpful as it can assist you in segmenting your customers into homogeneous groups so that you can implement clustering strategies. In this way, you’ll be able to tailor different aspects of your business strategy to the specific needs of each cluster.

A cluster is a group of customers with similar characteristics; you can create as many as you need. A practical case is customers according to their purchase behavior, paying attention to variables like frequency, quantities, the family of products, payment method, etc. This way, you can know better how your customers behave and create tailored strategies to reduce the churn rate by detecting when some customer is more likely to stop buying.

In short, what is the purpose of such clustering? It serves primarily to be timely because you can define touchpoints, products, prices, offers, etc., that best suit the purchasing habits of each cluster.

Improve the results of your marketing actions.

Clustering is not the only thing AI can do to help you achieve better results. It can also assist you in determining which marketing actions are most suitable based on the customer’s stage in the lifecycle. It does this by analyzing the history of your marketing actions and the results obtained. In addition to helping you execute winning actions, it also helps optimize decision-making time.

Some of the actions that can improve through the use of AI are tactics like cross-selling and up-selling. Primarily because it will help you offer products with a high probability of being purchased by customers who have selected or bought a product; this will significantly improve your average ticket value and generate greater customer engagement.

AI can also help you understand the reputation of your brand or products online. You can train Machine learning tools to discern between positive and negative feedback, allowing them to read through all the comments and provide you with the result. This way, you will know the impact of your actions and those of third parties on social media, customer service channels, etc. This valuable knowledge can help you determine which curse of action is most beneficial for your company.

Make production processes more efficient.

AI can help make your production plant more efficient. It is crucial when transitioning from corrective to preventive or predictive maintenance because it enables you to maximize the lifespan of machines and spare parts and avoid unexpected production shutdowns due to wear and tear. With the evolution of the maintenance strategy, you can efficiently schedule each action and minimize the impact on the continuous operation of production lines. You can learn more about this in our article: Discover how to improve the quality of your products with IIoT (Industrial Internet of Things).

In conclusion, we can say that AI facilitates data-driven decision-making, which positively impacts your company’s results. Similarly, it helps automate processes with benefits such as reducing the time invested and the number of errors.

If you’re interested in learning how to bring the benefits of AI to your company and don’t know where to start, contact us. We will help you clarify any doubts you may have and recommend the tools and solutions that best suit your needs.

IIOT helps you to improve quality

IIOT the key to improving the quality of your products

Industry 4.0, IIOT, or the Industrial Internet of Things (IIOT), is a crucial link in the evolution of production chains and the functioning of companies. It is because it helps close the information gap between what happens in the machines, production plants, and other areas of the company. When the industrial environment integrates into the digital business ecosystem creates the ideal scenario for synergies that lead the company to achieve new milestones of efficiency and competitiveness.


And how does IIOT work?


Industry 4.0 consists of connecting the machines, sensors, PLCs, and other devices in the production plant so that the data is stored in a data warehouse and analyzed for continuous improvement. Similarly, depending on the needs of each case, they can be connected so that the data streams in real-time and alerts prompt when the operation or performance is outside the desired parameters. These alerts help to take timely corrective actions, which reduce the total cost of managing production failures or errors.


In this aspect, Industry 4.0 helps companies to detect on time which part of the production process is failing. With more detailed and precise detection, you can fix errors affecting production efficiency and quality on time. For example, you can monitor indicators like temperature and humidity at different workstations and their variations. This way, it is possible to know precisely whether the production conditions are adequate to ensure the best quality.

The benefits do not end with general monitoring because it is also possible to relate information derived from machines with other information systems, for example, an ERP, to know the exact conditions for a specific customer’s order. It improves the company’s responsiveness in production and customer service, as it delivers the necessary information to the areas responsible for making management of product failures.


What impact does predictive maintenance enabled by Industry 4.0 have?


One of the impacts of Industry 4.0 is the reduction of maintenance costs. The main reason is that it reduces the non-availability times generated by taking the machines to the limit of failure, which is more typical of traditional corrective maintenance models.


According to Deloitte, predictive maintenance:
• Reduces the time required for planning by 10% to 50%
• Increases machine runtime and availability by 10% to 20%
• Reduces total maintenance costs by 5% to 10%


Guarantee quality products with IIOT


With the transformation towards Industry 4.0, companies improve their competitiveness for many reasons 1 of them is that they can guarantee that their production processes comply with the highest quality standards from beginning to end. It makes more sense when they understand that ensuring that machines are in optimal working condition contributes to delivering quality products by avoiding production errors caused by wear and tear. Especially those that may go unnoticed by other maintenance programs and are only evidenced when there are failures in the products delivered to customers.


Depending on the type of product, it is even possible to collect information on the operation of products already sold, which helps to offer a better after-sales service. This is useful when such products require maintenance or spare parts because they can be provided promptly, maximizing the life of the products and reducing non-availability times. This helps companies differentiate themselves from their competitors and improve their customers’ satisfaction.


What do companies need to move towards Industry 4.0?


The first step is to ensure that all the elements of the production plant that need to be connected are indeed connected. This includes not only the machines but also additional sensors that can report valuable information such as temperature and ambient humidity. Once this is done, it is important to define where the collected information will be stored and how it will be analyzed.


This final choice can make all the difference in how you can leverage the collected data. Tools such as DataGate IIOT can help you centrally manage all the information flows from your business and production environment for analysis using artificial intelligence. If you want a free demo of what DataGate IIOT can do for your company, contact us, and we will help you transform your business.

Benefits of sensorization for your factory

Benefits of sensorization for your factory

The number of sensors collecting information about our behavior and surroundings is increasing in the current context. They range from the gyroscope in our mobile phones, which helps to display images in the correct orientation, to motion sensors that turn on lights in some spaces. Industrial spaces are not the exception; more and more companies are adding sensors to their production processes. In this article, you will learn some benefits of sensorization for your factory.

Real-time comprehensive overview
You can access information about your production status as specific as room or machine temperature, which helps you to make better decisions on time. Enabling communication between machines and the enterprise´s digital ecosystem makes it easier to access reliable information.

Data-driven decision making
With data collected and stored, business leaders can analyze the historical records looking trends, and create work plans based on databased previsions. It helps increase the chances of success and improves efficiency reducing cost derivated from mistakes.

Preventive maintenance
Moving from corrective to preventive maintenance is a milestone for any company. But how does it work? It consists of scheduling maintenance when it makes more sense for the company. You can analyze the wear of spare parts, expenses, compliance requirements, etc. Collect all that data directly from machines and analyze it to determine the best time to do maintenance. This way, you reduce the impact of production stops.

Quality assurance
Another benefit of sensorization is that you can monitor the performance of machines and environmental conditions, such as humidity and temperature, to check they meet quality requirements. It enables a more reliable quality assurance process because the information comes directly from the machines. This way, you can tell apart the causes of any abnormality in final products.

Compliance friendly
Monitoring the performance of machines and environmental conditions is crucial to guarantee a compliance-friendly operation at your factory. By doing this, you can report confidently to authorities and control organisms.

Safer workplaces
Providing a safe workplace is a challenge for most companies, especially for those with employees working on high-risk or middle-risk tasks. In this matter, sensorization can help them to know if workplace conditions are safe for employees. Besides cutting down the number of accidents, it enables companies to be more efficient.

Product performance and after-sales services
Collect information from sensors installed in your products even after sales. This way, you will offer more customized after-sales service and learn how to improve your product performance.

How to get started? Where centralize all data collected?
With the perks of sensorization becoming more popular, more companies are interested in learning how to get started.
Here are some pieces of advice:
Determine how many sensors you need. You can define criteria based on what data is appropriate for your business and production model. With that task completed, move forward, and determine how to process data and where to store it.
In this sense, we recommend DataGate, a Data Hub + AI, that allows you to collect and store all the data generated in the machines with multiple benefits like process simplification and the suppression of the unavailability window. If you want to learn more about this tool, contact us, and we will help you make the intelligent sensorization of your company a reality.

Challenges and opportunities when working with high volumes of data

Challenges and opportunities when working with a high volume of data

The increase in the volume of data companies are working with is a long-term trend. That growth happens at a different speed in every industry, but none is safe from the exponential growth of the information they use. This trend is two faces of the same coin. On the first side are challenges, and on the other side are opportunities. We will lead you through the main challenges and the opportunities that might result from carrying out challenges properly.


Challenge: Is it necessary to back up every piece of information?

The quick answer is no. But the only way to find the right path is to take time to create a data strategy aligned with your business plan. This strategy must contain what the company needs to operate in the present and future. Well-defined criteria are crucial in this matter.

Back up unnecessary data will make company information structure and increase all derivated costs. Additionally, because it is irrelevant data, it will not add up, becoming impossible to obtain any benefit to cover the derivated costs. If, on the other hand, you do not back up essential data, the company perspective will be biased, and decisions will lack trust.

Opportunity
Saving the appropriate data nurtures a work environment advantageous for data use. Counting with the proper data sets enhances the company´s vision and improves competitiveness by making it easier to access data. It also helps predictive analytics accuracy because data volume is a crucial factor. It enhances the creation of business plans with a higher success rate.


Challenge: What is the best option for data storage?
When choosing data storage, you should evaluate factors like storage size, growth speed, scalability, security, and availability.
Every company uses as many data sources as they need and tend to be different. It is another aspect to keep in mind when making a decision. The core reason is that it should guarantee seamless integration within your whole digital ecosystem. Ignoring this point can result in a disconnected data source or the necessity of acquiring new connectors, which implies new costs.


Opportunity
A data storage option that meets changing business needs allows for keeping the company competitive by supporting data availability. Choosing a convenient data storage option helps to keep optimal answer times and avoid slowing or stopping processes related to data in the company.


Challenge: What updating data model is the most appropriate?

It is a question you need to answer almost at the same time when choosing your data storage. In this matter, you need to define how frequently you will run updates on the data warehouse. Also, decide if data updating will be active or passive. In other words, updating will happen every time there is a request or not. In the last case, it is essential to schedule it according to the data volume, type, and dynamics of the business itself. The principal criterion for making this decision should be the company. For example, if your team needs information from the same day to provide attention to your clients, you should go for passive updating. That is, it is updated every time a query is made. In this way, the data will correspond to the date and time of the consultation and not, for example, the previous day.
If, on the other hand, there is no need for access to the latest version of the data, an active update can be set, for example, once a day. It optimizes storage and upgrades resources. This option is helpful when working with high volumes of data, for example, national-wide sales reports of supermarkets chain.


Opportunity
The right choice will help to use resources wisely and not hinder business operations. It allows you to keep your costs low, and your business will perform seamlessly.


Challenge: How much invest in data management?
The core of this challenge lies in finding the criterion that fits better. Commonly, have to answer for tool selection, license acquisition, etc. So we share a crucial touchstone to transform this challenge into an opportunity.


Opportunity
The exact investment will vary from company to company, but the main criteria should base on a vision that points to an operation that contributes to a healthy ROI (return on investment). The value that current society gives data grows exponentially, which is why proper management will positively impact the P&L (Profit and Loss) balance. This value lies in its contribution to a more accurate decision-making process. Based on business-specific information, which reduces the impact of human biases. Having the tools to manage the data is essential to materialize this use.


We recommend two tools that help you bring the opportunities presented to your company. Leave data silos behind and centralize your entire digital ecosystem in a data hub powered by artificial intelligence, such as DataGate. Plus, get innovative insight into data with the business intelligence tool BI4Web. If you want to know more about these tools, contact us. We will help you start your path toward profitable management of your data.

Barcelona connectivity-min

RCM Software at Mobile World Congress in Barcelona 2022

We start this 2022 with excellent news, we will be participating at Mobile World Congress for the fourth time, three of them in Barcelona and one in Los Angeles.

Visitors will have the chance to get to know RCM Software novelties first hand, in products such as BI4Web and DataGate. With a special emphasis on Data Gate, our tool represents huge support for companies that are looking for an ally in their fourth revolution path. DataGate extracts data from any data source, this includes PLCs and processes it with machine learning algorithms. This way, companies can keep high-quality information to make decisions based on data, improving availability, performance, and quality.

We encourage our clients, partners, and companies interested to visit us at CS180 stand between February 28th and March 3rd. in Fira Barcelona.

Empleado con tableta-min

Improve your production standards with IoT

The fourth industrial revolution is changing many things, but there are things that never change, for example, the KPI definition and the efficiency quest. In this context, tools and solutions play a very important role when collecting data straight from machines and delivering important information.

However, data collection is not enough. It is necessary to have a wide and clear panoramic for defining actions needed to achieve full improvement. A key step in this path is defining KPIs, for example, overall equipment efficiency or OEE, which is useful for measuring the time a machine is producing at its maximum capacity and with optimum quality.

This metric take into account three key factors: availability, performance, and quality. Keeping a record of these factors has a positive direct impact on OEE since it helps to identify where losses are happening. For this reason, IoT tools and solutions become allies that represent a big advantage. Here are some of them:

Availability: Moving from corrective maintenance to a preventive and smart one

It is impossible to avoid unavailability periods in machines since they need to be fixed once in a while, but it is possible to reduce those periods with preventive maintenance based on information extracted from machines like working records and waste derivated.

With solutions like those offered by DataGate, it is possible to collect data from machines and store and analyze it. This way, you can know in advance when it will be necessary to schedule maintenance and not to do a corrective one, which tends to take more time since it is necessary to find out what happened, request the necessary pieces, and then do the actual maintenance.

This is possible thanks to diagnosis based on machine learning done with data extracted from machines such as temperature, engine vibration, and other parameters. This way any deviation of parameters might work symptoms of a failure in the near future.

In the same way, IoT sensors can tell in real-time the actual amount of available materials, so the machines do not have to stop because of a lack of them.

Performance: Achieve and keep optimum performance levels

Besides regular maintenance, there are some other short stops in production that can be related to materials stuck or components dealignment. These stops use to be ignored because of their fast resolution and small impact in the immediate term. However, the accumulation of this kind of event might turn into performance reduction or hide a bigger problem.

With IoT, it is possible to know accurately where the failure occurred, and what parameter is out of range and this way find a timely and proper solution. Additionally, keeping a record of all regenerated data enables a full view of incidents with details like how frequently occur and how much time was required to solve them. This information helps teams to make better decisions, based on data, improving performance by eliminating or mitigating chronic issues.

On the other hand, IoT helps to keep speed production at adequate levels, because it is possible to know if any factors such as lack of lubrication, environmental temperature, or dust are slowing down machines’ performance. Offering a 100% accurate answer to the reduction of indicators such as OEE.

Quality: From beginning to the end

Quality is another element part of OEE, taking into account it depends on many factors it is very important to quantify them and see their impact on the final result. It is in this matter that DataGate delivers a remarkable value because allows measuring variables of the own machines and other externals like environmental temperature that may influence in product´s quality.

An important moment to implement improvements is when machines are starting production since usually defective products are made within this first moment. These improvements can be designed from learnings generated from machines’ data analysis and collection.

In conclusion, working with a solution such as DataGate makes possible radical improvement of OEE because of the first-hand access to real-time and historical data, delivering relevant knowledge of different work fields. This knowledge is the fundamental base to make informed and timely decisions that contribute to reaching an OEE as close as possible to 100%.