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Gone are the days when tables were created manually. Today, production plans are digital and managed using specialized computer applications and systems. As a result, there is a growing demand for AI-powered production control systems. What are the benefits of using AI in production management? In this post, we will present why organizations decide to implement artificial intelligence in production management, what are the benefits of doing so, and we will present examples of its practical application.
The purpose of control in the production process
Production control focuses on monitoring production activities in order to achieve cost efficiency and ensure high quality. It also deals with the optimization of the processes of “production” and “sale” of products, which is crucial in the manufacturing sector.
Organizations manage a wide range of manufacturing operations, including raw material procurement, inventory management, supply information, and transportation methods. The scope of management in this area is extensive and the tasks are extremely complex. Production management systems support companies in conducting these complex operations.
Benefits of using AI in production management
Artificial intelligence (AI) is gaining importance in the context of production management. Before the AI era, organizations faced numerous challenges in managing manufacturing operations, even after implementing manufacturing management systems. Balancing the workload between different departments required effective division of staff and coordination of activities between departments.
In addition, the management of raw materials, submaterials, work-in-progress and outsourced parts was carried out through production control. It is worth noting that there is always a risk of oversights in arrangements and errors in orders.
Industry demand forecasts and defect rate assumptions were often unpredictable or based on experience and intuition, making production management a highly dependent task on the skills of those responsible. Unfortunately, personalization often had a negative impact on the quality of work. The emergence of artificial intelligence in the area of production management has opened up opportunities to solve these problems. Better control and greater forecasting accuracy are important steps on the way to improving production management processes. That is why AI-based solutions are increasingly being used to increase the precision of production operations.
So what are the benefits of implementing artificial intelligence in production management? Let’s take a closer look at this issue.
Minimise staff shortages and dependency on individual competencies
Production control operations often depend on the competence of the supervisor, which can lead to an increased workload. The manufacturing industry is facing staff shortages, which further increases the pressure on production managers.
The implementation of an AI-based production management system can significantly reduce the amount of manual work that managers have to do. The implementation of AI makes it possible to reduce dependence on individual competences and reduce the workload of each employee, which contributes to the elimination of the problem of insufficient human resources.
Demand forecast based on massive data analysis
Creating production plans based on demand forecasts is a key element of production management. The traditional approach, based both on the experience and intuition of the person in charge and on the analysis of the information collected so far, requires a significant level of expertise.
The introduction of AI opens the door to processing vast amounts of data and information in a short period of time, while making it possible to identify patterns for those aspects that previously relied mainly on intuition without a solid foundation. The availability of more information is conducive to more accurate demand forecasting, and artificial intelligence, through continuous learning, can significantly contribute to increasing the accuracy of these forecasts.
Responding to changing needs through flexible and fast adaptation
The days of mass production of a limited number of models are over. Diverse market needs are best met by low-volume production with high variability (high-mix). However, there are limitations related to resources such as personnel, location and equipment in factories, which makes it unachievable to prepare individual production lines for a wide range of products. Thus, flexible production management and the ability to quickly adapt production plans in response to changing needs become crucial.
Implementing artificial intelligence (AI) can significantly reduce the burden of continuously adjusting production planning while improving its precision. In the face of rapidly changing needs, the role of AI is becoming increasingly important to enable organizations to keep pace and flexibly adapt to new production requirements.
Precise real-time information sharing
The information that needs to be shared with different departments is changing rapidly due to evolving needs and constant adjustments in production management. As manufacturers continue to strive to improve production efficiency, even minimal delays in communicating information in production cycle management processes, measured in fractions of a second, can lead to the risk of significant waste. Hence, many production control systems have been equipped with information and data sharing functions.
The introduction of artificial intelligence significantly increases the volume of information and data that can be processed, which highlights the importance of real-time information exchange. Thanks to AI, it becomes possible not only to speed up the process of data sharing, but also to significantly increase the accuracy and timeliness of the information provided, which as a result contributes to a more efficient and synchronized management of production operations.
How to implement AI in production management in your company
To take advantage of the potential of AI in production management, it is essential to integrate a production management system with AI technology. If you haven’t installed a production control system yet, you may want to consider implementing one. If, on the other hand, you already have a production management system in place, but you don’t plan to incorporate AI into it, it’s worth considering changing the system.
When implementing a new system, you will have to make several decisions:
- Development method: Choose whether you will purchase a ready-made system package or decide to develop your own solution.
- System Location: Decide whether the system will be managed locally on your servers or in the cloud.
- Data migration: Develop a strategy for transitioning from your current system to the new one.
When implementing a new AI-based production management system, it will be crucial to develop data collection functionalities aimed at improving the efficiency of processes. Adequate data quality and integrity are essential to fully exploit the potential of AI.
Examples of production management using AI
There are several cases where production management started with partial AI. For example, the use of AI advances in the following operations:
AI in the production planning process
Developing a production plan is one of the biggest challenges in production management. While traditional manufacturing management systems can organize, integrate, share, and visualize information, final planning often requires manual intervention.
For example, a large food company invested in an AI-based production management system, using AI to develop production plans. A mechanism that enables AI to learn from manufacturing management experts calculates an optimized production plan for that company.
Thanks to machine learning capabilities, AI now makes it possible to formulate production plans with a high degree of accuracy, surpassing manual planning. AI not only increases efficiency, but also brings a new level of precision to the planning process, which is of great importance for optimizing production processes.
Optimize production and manage inventory with AI
Many production managers tend to maintain high inventory levels to minimize the risk of product and material shortages. Such caution, although understandable, can gradually increase operating costs.
A company decided to invest in an AI-based production management system, which allowed it to reduce excess inventory, which was the result of human caution. Artificial intelligence can identify the optimal inventory level, which in turn allows you to determine the ideal production volume and develop an efficient production schedule. By using AI, the company has been able to minimize costs without exposing the production process to the risk of stock shortages.
Forecasting demand and adapting plans in response to changes in the environment
Beverage sales can fluctuate depending on weather conditions, complicating the demand forecasting process. This beverage manufacturer decided to use artificial intelligence to improve production management.
In the past, demand forecasting was difficult due to external factors such as weather conditions, which required human analysis as machines were unable to take this into account. However, with the help of artificial intelligence, it is now possible to allow the system to take external factors such as the weather into account when developing production plans. Thanks to AI, production planning has become more precise and more resistant to changing environmental conditions, which in turn has a positive impact on the efficiency of the entire production process.
Improving Quality Control with AI
The quality control process often involves the need to perform many tasks manually. The challenge arises when inspectors find it difficult to carry out inspections according to uniform standards. For example, in the case of visual evaluation, subjectivity is inevitable, and it is difficult to completely eliminate discrepancies in evaluation. In addition, it is possible to overlook defective products.
However, there are successful cases of AI being used in the quality control process. In one of them, images captured by cameras are compared with the collected data on acceptance criteria, and artificial intelligence performs an automatic assessment. As a result, assessments are made with an accuracy far beyond the capabilities of human inspection. By automating the quality control process, AI not only increases the consistency and accuracy of evaluations, but also significantly contributes to the overall level of product quality.
AI advances in manufacturing management
In this blog, we’ve outlined how significant changes can be achieved by integrating AI into your manufacturing management processes, and how you can improve the operational efficiency of these processes.
Production management is an extremely complex task, covering a wide range of aspects of production activities. It requires the processing of vast amounts of information, and the human ability to handle low-volume, high-variation production is limited. As a result, more and more attention is being paid to systems that integrate artificial intelligence into production management systems, enabling machines to optimize solutions based on an extensive database.
- Process Automation and Optimization: AI can automate numerous manufacturing processes, reducing the time and errors associated with human intervention. It can also optimize processes by identifying the most effective methods of operation.
- Forecasting and Planning: AI can analyze large historical data sets to predict demand and help with production planning. It can also predict future changes in the business environment, which enables organizations to be better prepared for future challenges.
- Quality Control: As mentioned earlier, AI can significantly improve quality control processes by automatically identifying product irregularities or defects early in production.
- Inventory and Supply Chain Management: AI can analyze data in real-time to help with inventory management and supply chain optimization, leading to reduced costs and improved operational efficiency.
- Multivariate Analysis and Simulation: AI enables multivariate analysis of production data and simulation of different scenarios, which helps to make better operational decisions.
- Personalization of production: AI enables low-volume and individualized production at scale, enabling faster adaptation to changing consumer preferences.
- Training and Support for Employees: AI can also offer training and support to employees in real-time, helping them solve problems and improve their skills.
- Integrated production eco-systems: AI can support the creation of integrated manufacturing ecosystems that connect the different elements of the manufacturing process, from procurement to distribution.
Introducing artificial intelligence into production management opens the door to extraordinary opportunities. Companies can now explore new horizons of efficiency and innovation, ultimately leading to better efficiency, lower costs, and greater customer satisfaction.
Autor: Tomasz Matuszek; Dział Marketingu - Firma Gulajski