Operational optimization is not an option; it is a constant necessity for any industrial company seeking to be more competitive and profitable. According to a report by Deloitte, 35% of the operational costs in the industry come from inefficiencies in processes. Factors such as rising energy costs, the pressure to meet delivery deadlines, and the need to maximize productivity have led organizations to rethink how to improve their production processes.

The implementation of technologies such as AI in predictive maintenance or digital twins to simulate and optimize infrastructures allows companies to identify areas for improvement and make faster, more precise decisions. In the face of these challenges, optimizing production processes is key to transforming operational efficiency into tangible results.

What is production process optimization?

Industrial production processes are the set of structured operations and tasks that allow the transformation of raw materials into final products. The optimization of these processes consists of identifying and eliminating inefficiencies to maximize productivity, reduce operational costs, and improve operational efficiency in the industry. There are different types of optimization depending on the approach: from production flow optimization, focused on eliminating bottlenecks, to energy efficiency in production processes or the implementation of digital twins in the industry. These processes are typically developed in key stages, such as initial diagnosis, solution implementation, and continuous improvement. However, before optimizing, it is essential to identify the productive inefficiencies that limit the performance of companies. Below, we explain how to detect and resolve them practically.

How to identify productive inefficiencies.

Detecting and resolving productive inefficiencies is the first step toward optimizing industrial processes. If you are looking to improve the operational efficiency of your company, you must follow a structured process to identify weak points.

Step 1: conduct a diagnosis of current processes.

The first step is to conduct a thorough analysis of the current processes. It is essential to identify how tasks are being executed, what resources are being used, and what results are being achieved.

1. Perform a process mapping to visualize each stage of production.

   
   

2. Collect key data on production times, consumed resources, and possible delays.

   
   

3. Extract key metrics such as OEE (Overall Equipment Effectiveness), or “Overall Equipment Efficiency,” by its acronym in English.

To do this, TOKII has the capability to diagnose and resolve inefficiencies by combining real-time monitoring, historical data analysis, and the ability to create your own customized metrics. In addition, it facilitates the comparison between the current situation and the desired objectives, allowing informed decisions to improve performance and optimize operational efficiency.

Step 2: Identify improvement opportunities.

Once the processes have been diagnosed, it is essential to identify the bottlenecks: stages that slow down production or generate waste. These may include:

• Equipment operating below their production capacity.

• Excessive waiting times between processes.

• Lack of synchronization between machines or equipment.

  
  

At this stage, TOKII employs visual analytics techniques to detect patterns, identify bottlenecks and inefficiencies, and propose improvement opportunities. To do this, we rely on tools that we have developed using artificial intelligence, machine learning, and big data to quickly and accurately structure and analyze large amounts of information.

Step 3: Technological implementation

Now that you know which leg your production chain limps on, it is necessary to use the right tools to correct and optimize those processes. If we take one of the problems from the previous point, we can extract the following example:

The first of these is very common in the industry: equipment that does not achieve its maximum performance due to unexpected failures, lack of efficient maintenance, or underutilization. To solve this, we could incorporate solutions based on AI and ML with the aim of performing predictive maintenance of assets.

For example, TOKII performs real-time simulations using digital twins integrated with the IoT sensors of industrial machinery with the aim of anticipating failures and improving the individual productive capacity of each machine as well as the global production of a factory.

Additionally, TOKII incorporates an alert system that can notify personnel at the right moment if any machine shows irregular performance patterns, recommending preventive maintenance actions and thus preventing production losses.

Step 4: Measurement and continuous improvement

Once the bottlenecks have been identified and the solutions implemented, it is important to measure the results obtained and apply a continuous improvement process to ensure that inefficiencies do not reappear.

With TOKII, the system is constantly fed back with the feedback it collects, so that, as the twin learns from the processes of its physical counterpart, it adjusts its predictions and analyses, becoming increasingly accurate and realistic. This continuous learning guarantees the efficiency and precision of operations.

You can establish performance indicators such as OEE, production cycle time, energy efficiency, and production rate. Monitor this data, adjust, and optimize each process constantly until maximizing the performance of your factory.

With TOKII, you can make use of interactive 3D dashboards that allow you to analyze KPIs in real-time, or access your traditional 2D data panel.

Methodologies to optimize industrial production processes

Smart Factory: an intelligent factory to identify and solve operational inefficiencies

The Smart Factory represents the evolution of the industry toward digitized and connected production plants, capable of detecting, analyzing, and correcting inefficiencies in real time thanks to its ability to collect and process large amounts of data from IoT sensors installed in machines and equipment.

TOKII acts as a comprehensive solution that transforms traditional factories into smart factories. Combining real-time data analysis with digital twin technology.

 TOKII provides total visibility, control capability, and optimization of production processes, helping to quickly solve inefficiencies and anticipate potential problems before they impact production.

Lean Manufacturing: eliminating to optimize

While the Smart Factory provides visibility and control in real-time thanks to technologies like IoT and digital twins, Lean Manufacturing establishes a methodological foundation to identify inefficiencies in a structured way and optimize workflow.

Using TOKII, you can map the value flow, detect the source of the problem, and simulate a new, more efficient workflow. In this way, you eliminate waste and achieve a smooth and synchronized production.

In combination with Lean Manufacturing principles, TOKII not only helps to detect and eliminate waste but also guarantees the continuous improvement of production processes, allowing industrial companies to reach their maximum operational efficiency potential.

Common industrial processes with the greatest opportunity for improvement

Unscheduled interruptions due to lack of maintenance

Unscheduled interruptions are one of the biggest challenges for industrial companies in Spain. It is estimated that the average cost of an unscheduled interruption ranges between 1000-50000 euros per minute. This figure is even more alarming when 68% of companies report having experienced significant or moderate interruptions due to bottlenecks, while nearly 29% had to stop production for at least 20 days due to a lack of essential components.

To prevent this from happening to you, TOKII has an AI and Machine Learning-powered module that identifies anomalous operating patterns in machinery, anticipating problems such as part wear, mechanical failures, or operational mismatches. Moreover, due to its digital twin technology, it simulates the behavior of the equipment in a virtual environment that can be monitored remotely and alerts operators to plan a well-timed maintenance operation.

Energy efficiency and resource wastage

Energy efficiency is a critical aspect of the Spanish industry, both from an economic perspective and due to the pressure to comply with decarbonization and sustainability regulations.

In sectors such as manufacturing and metallurgy, energy and natural gas can represent up to 40% of operational costs, meaning any inefficiency incurs significant economic losses. Problems such as machinery wear, misaligned systems, and the lack of real-time monitoring lead to unnecessary consumption and resource wastage that impacts the profitability and productivity of plants.

TOKII improves energy efficiency by integrating IoT sensors to collect and analyze real-time energy consumption data, identifying areas with excessive consumption and proposing precise adjustments to reduce waste.

For example, if a production line shows abnormal energy consumption due to misaligned equipment, TOKII alerts the technical team and suggests the necessary corrective actions to optimize consumption. In this way, companies not only reduce their energy costs but also improve their operational efficiency and contribute to more sustainable and competitive production.

How to improve industrial production processes using digital twins: real examples.

Manufacturing sector

SIDENOR has successfully optimized its production processes through the use of intelligent alerts powered by artificial intelligence. These alerts can detect anomalous behaviors in the data without requiring users to configure alerts manually.

TOKII continuously monitors real-time processes, analyzing data patterns that may go unnoticed by the human eye. This constant monitoring allows users to be more at ease, as the alerts automatically notify the user when something is not functioning as it should, enabling timely action before things develop into a problem.

Thanks to this technology, SIDENOR has reduced response time to incidents, optimizing resources.

Steel sector

VICINAY faced the challenge of integrating and organizing data stored over 20 years across different applications, accessing the information with unintuitive and non-interactive tools.

Previously, tasks such as sending invoices, reports, and other documents required a person to spend time collecting and sending data manually. Now, with the integration of TOKII, VICINAY's clients can directly access this information, generate reports, and visualize all relevant data in a centralized way.

This change has not only significantly reduced the time spent on administrative tasks but also increased transparency and autonomy for clients by providing them immediate access to the data they need. In this way, VICINAY has improved its internal production processes while offering a more agile and efficient service.

Machine-tool sector

TOKII plays a crucial role in optimizing production processes thanks to its integrated calculator for simulation and analysis, which allows DIMECO to provide its clients with the necessary support for configuring their production lines. Previously, this calculation was a long and repetitive manual process. Now, it is completely automated thanks to TOKII.

DIMECO's clients can easily access the intelligent calculator integrated into the digital twins, simulating specific scenarios that enable them to configure and adjust their production lines based on their objectives through the use of machine learning and artificial intelligence.

The ability to simulate scenarios and calculate configurations saves material resources and minimizes errors. In this way, DIMECO has optimized its internal production processes and improved its clients' experience.

Tools to improve industrial productive capacity

When optimizing industrial production processes, there are various tools and methodologies that companies can implement according to their specific needs and resources. From operational approaches like Lean Manufacturing to advanced digital twin technologies, each solution brings specific advantages and is oriented to address different production challenges.

Benefits of applying digital twins to improve the operational capacity of industrial companies

Unlike individual solutions such as simulators, ERP, or software, which address problems in isolation, digital twins, like TOKII, represent a comprehensive and advanced solution for optimizing industrial production processes. TOKII combines technologies such as IoT, artificial intelligence (AI), and Machine Learning, eliminating the limitations of other tools. While many traditional solutions require long implementation periods and highly qualified personnel, TOKII is ready to be used intuitively, accelerating its integration into daily operations without interruptions.

Trends for 2025 in the industrial sector

Emerging trends for 2025, backed by consulting firms like McKinsey and Deloitte, highlight the importance of digitalization, artificial intelligence, advanced automation, and the circular economy as fundamental pillars for the industrial future.

Digital transformation remains a priority. Deloitte points out that manufacturing companies are investing in digital infrastructure, data analysis, and IoT to address critical issues such as supply chain interruptions and the lack of specialized talent.

It also indicates that by 2025, 25% of companies will implement generative AI agents capable of automating complex tasks with minimal human intervention. This will represent a significant leap in operational efficiency and reduce costs while improving decision-making accuracy.