Digital maturity assessment of companies and its operations
DigiAudit – a comprehensive, technologically independent questionnaire – a standardized process that takes small and medium-sized businesses the first steps toward digitization We developed the DigiAudit methodology in cooperation with our partners. However, we place great emphasis on the fact that DigiAudit is completely independent of specific technology suppliers. The first step is the digital and AI maturity questionnaire – the basis for structured interviews with the company’s management and a guided discussion in the form of targeted questions. It introduces assessors to specific areas of companies and prepares the ground for additional questions.
The processing of evaluations is divided into two parts. Evaluation part and design part.
In the evaluation phase, general information is collected, motivation and priorities are assessed, the level of process digitization and AI technologies is evaluated, processes with potential for improvement are identified and the technology is thoroughly mapped.
The design part summarizes the results, creates benchmarking and designs a roadmap to increase the digital maturity level. Subsequently, the outputs are summarized in the feasibility study and presented to the selected company´s management for comments and approval.
The results are consulted in detail and management of the selected SMEs are learning about our findings.
The resulting digitalization plan tailored-made by our experts helps SMEs to boost their digital and AI performance and skills in the following ways:
Management should learn how to assess the digital and AI maturity of their company, and how to identify those areas in which to invest. Further, management shall be able to evaluate the financial demands of the solutions, their returns and economic benefits for the future operation
Management will learn about the technical possibilities, suitable for their company
CIIRC CTU aims to help the SMEs in their way of digital and AI transformation from low-cost subcontractors to independent and flexible digital and AI-based organisations with high value-added production.
The aim is not only to identify areas of the companies to increase their digital level but to identify those areas in which “as little financial and time investment as possible” will increase the company’s competitiveness as much as possible by increasing its digital and AI level
Provide SMEs with clear and comprehensive information about the technical complexity of the solution, its return and economic benefits for the future operation of the company, and, thanks to a comparison with the benchmark of the industry, increase its competitiveness
Provide the selected SMEs with the resulting digitalization plan that would comprehensively summarize the selected company’s survey findings, and proposed solutions and would place them in the overall context and conditions in which the company operates, so that our recommendations would lead to increased digital level, competitiveness and resilience in the ever-changing global market.
Show SMEs the way to effective digitization, to set the right direction at the crossroads of many possibilities.
Development of comprehensive digital twins of robots/machines and processes for virtual robot/machine simulation, commissioning, and process optimisation (cyber-physical systems). Easy-to-use commissioning and operating on the shop floor with assistance systems, e.g. virtual and augmented reality development, smart projection systems etc. and digital twin support for shop-floor operation decision making. CPS-upgrade of production sites: development of suitable solutions to connect many different sources, aggregate data (e.g. agent-based solutions) and provide human-understandable information.
Cognitive robotic manufacturing systems allow you to take automated production to the next level. By using standing perception systems, robots can adapt to a specific situation. The robots are no longer limited to performing a repetitive sequence of programmed movements, but instead, control their movements according to the actual requirements. Such robots can be used for handling loose objects, e.g. for removing parts from shipping boxes or for assembly tasks where minor shape deviations need to be solved by correcting the robot’s trajectory.
Flexible scheduling and simulation of the production process with uncertain input data and with inputs from the real process. Production as an interconnected ecosystem of productions sites, logistics & customers, autonomous distributed decisions & production plans Production as a service – next stage of distributed production Making use of the equipment of the Testbed for Industry 4.0
Design and deployment of AI for manufacturing monitoring and control; Industrial knowledge mining from various data sources based on advanced deep learning and complexity reduction techniques; Emphasizing modularity in the organization of the manufacturing lines to transform the production towards greater flexibility, dependability and reliability. This goes in hand with the capabilities of machines to negotiate best possible setting and production sequence, according to the principles of multi-agent systems. Autonomous reconfiguration and adaptation by means of service-oriented architecture that allows matching of the product qualities, production recipes, and production components capabilities needs to be designed. Planning and Scheduling to optimise processes and to react to changes and disturbances along the supply chain.