Automated task allocation competency-based model

• Κύριος συγγραφέας: Γιγής, Γεώργιος
• Άλλοι συγγραφείς: Gigis, Georgios
• Γλώσσα: English
• Έκδοση: 2021
• Θέματα: Competencies; Task allocation; Ικανότητες; Χάσμα ικανοτήτων; Κατανομή εργασιών; Βελτιστοποίηση διεργασιών; Χρονικός προγραμματισμός

Industry 4.0 has created several challenges for the human element in the working environment. With the Industry 5.0 emerging, the workforce receives an even more necessary role, of integrating the technology to the everyday operations of a production unit and ensure that the adoption of novel solutions is successful, while on the same time change their role, from performing tasks to innovating and solving complex problems. Taking into consideration that the human operator shift their focus to more creative and strategic jobs, the task allocation process will face new challenges and technological advancements should provide solutions for them. Now, jobs are assigned to people based on the supervisor’s intuition and judgement, wasting important time from defining the task till finding the most qualified employee for the specific job, and lacking documentation of the decision-making process. Although, competencies have been discussed thoroughly over the past few years, there is still room for improvement in measuring and comparing different competencies of human operators, engineers, technicians, and using the results to manage human capital. To uncover the potential of the task allocation, process the competencies will be used as decision-making criteria, aiming to achieve the best possible performance, through an automated system to assist the project manager find the optimal division of tasks to the available human resources, based on their competencies. The proposed framework can be applied both on a project and on a production line because it can be performed with real-time data and task allocation methodologies are the same for them, with the only difference being the task duration. In order to validate the applicability of the proposed framework and the generated algorithm, a case study derived from a maritime company has been examined, with the objective to allocate in the optimal way seafarers to vessels and maintain a balanced competency level among the fleet.