Companies must respond to the ever-increasing demands of their clientele and heightened competitive pressure. Particularly when it comes to production and order management, the many influencing variables pose special challenges for the decision-makers. However, the changing environment is not easily understood – adaptive systems are needed that can learn from past data and provide accurate forecasts to support decision-making for new, unknown situations.
INIT combines everything under one roof. Our interdisciplinary consulting teams are able to achieve maximum benefits for our customers. We can draw on expertise in auditing, mathematics, development as well as consulting with many years of industry knowledge. This gives us a comprehensive 360° view of your current situation and allows us to analyze, discuss and optimize a wide variety of aspects.
“We accompany you on the way from local to global maximum to Smart Company – step by step.”
Armin Aigner, AI expert at INIT
Get a recipe for success that will put your company ahead of the international competition. The focus of the project is not on local stand-alone solutions – such as individual plants or production lines – but encompasses an overall view of your value chain and thus sharpens the senses for global interrelationships:
Using an iterative approach, we work with you to develop the specific requirements, steps and resources needed to deploy artificial intelligence in different areas of your business. Viewing the company as a multidimensional entity brings the subsequent optimization potentials into focus:
AI is changing production processes and value chains worldwide. The alignment of the company’s goals with the value chain defines the company-specific mathematical basic model, on which the development of the industry-specific company model of the AI control center is based. This stands for:
Part of the scoping is the inventory and the potential analysis. Processes and tasks within the company are analyzed and scopes of investigation are defined. The focus is on complex planning, management and manufacturing processes. Depending on the size and requirements of the industrial company, the scope and duration of the project can be estimated precisely at the outset.
To sharpen business understanding, problems within the value chain are identified and analyzed. By formulating various questions, goals are defined that can be achieved using AI methods.
The influence of various IT systems, processes and key figures on the corporate formula and their interdependencies are examined and elaborated.
The data provided is the basis for the development of the company-specific algorithm. Data collection is divided into the following process steps:
ETL: Data transformation
Data collection (sensor data, raw data)
Industrial plant / production landscape
There needs to be a common understanding of the following:
The development of an enterprise model depends on the goals and the processes. With this basic understanding, mathematical modeling is tackled. The creation of the model is process-oriented and consists of the following steps:
Models – selection of algorithms and methods
A permanent use of the results, the reaction to changed framework conditions or extended scenarios require a constant adaptation. By evaluating the current status, appropriate adaptation requirements are derived or implemented:
The enterprise model is based on parameters that are subject to change over time. Therefore, situational updating of parameters is of high value. The following questions are designed to identify answers that justify a realignment of parameters:
The pivotal point is always the respective company, which determines the extent to which the model is to be successively expanded and thus the company’s results improved. Presentation and review of the achieved results form the foundation for potential further sprints.
Please feel free to contact us!
“I would be happy to discuss the benefits of KI-Leitstand for your company.”