The Scedas Timekeeper software tool developed by the Fraunhofer CML (Fraunhofer Center for Maritime Logistics and Services) records tasks in a structured manner with little additional effort, in addition to recording working hours. Employees use the time recording tool to document their working hours on a task basis. At the end of the working day, they can enter in a desktop app which tasks they have worked on and for how long, or record the daily tasks in a smartphone app or web application. Possible tasks are categorized in advance so that employees can choose from different lists. If desired, employees can add their own tasks to the selection. The task-based working times create a basis for data-based optimization.

More transparency thanks to business intelligence
Working times enable data evaluations, a valuable basis for strategic decisions. Sceda's Timekeeper records operational workflows and visualizes them on a company-specific dashboard. On this basis, work processes can be improved, tasks redistributed, tours optimized or the need for additional qualifications examined. Analyses of this data create transparency on the one hand and a well-founded control option on the other. Great importance is attached to protecting the personal rights of employees: Sensitive personal data is anonymized and aggregated as part of the analyses. The tasks performed can only be traced back to the position and not to the individual employee.

Automated personnel and maintenance planning
The recorded work processes also provide data-based support for personnel scheduling and maintenance planning. The Scedas planning software calculates situation-specific personnel requirements and automatically creates deployment plans. The algorithms schedule company-specific tasks as well as regular maintenance tasks in compliance with working and rest times. Scedas Timekeeper facilitates the one-time setup of Scedas by providing information about the tasks to be scheduled. Scedas is tailored to specific industries and can respond to the peculiarities of logistics processes. It is already being used by several shipping companies in the maritime sector. The planning algorithms translate a sea voyage into a sequence of work processes, such as receiving the pilot, docking in port or taking on fuel, and calculate a personnel key for each sea voyage and generate deployment plans for the crew at the touch of a button.

Intelligent maintenance management
The maintenance of components is a time-consuming and costly part of logistics. Time recording provides data-based answers to maintenance management questions. Sceda's Timekeeper records the execution of maintenance tasks in a structured manner. Analysis of this data provides support in maintenance management. An overview of how much unplanned maintenance occurs on average, how long the various maintenance tasks take on average and who carries them out makes it easier to set maintenance targets.

A further step is to use the recorded maintenance data for condition-based maintenance. Sensors can continuously monitor the condition of technical components. Data on unscheduled maintenance or even failures can be linked to the condition data of the components. This enables data processing methods to evaluate the combined data and recognize patterns in it. These patterns and continuous condition monitoring enable favorable maintenance times to be identified at an early stage. Algorithms can also use data to predict the service life of the component depending on its technical condition.

The authors: M.Sc. Celien Bosma and Ole John, Nautical Engineer and MBA (Head of Department at the CML)

www.cml.fraunhofer.de