Method for diagnosis and/or maintenance of a transportation system in view of optimizing replacement and maintenance intervals so that full lifetime is used and no functional failures shall occur, said transportation system having at least one transportation device and a remote monitoring unit being remote from said transportation device, said transportation device having a control board for controlling and/or monitoring a function of said transportation device, and a local control unit for controlling and/or monitoring said control board, said method comprising: - detecting raw data connected to said at least one function at said control board and/or said local control unit; - generating condition information and/or performance information based on said raw data at said control board and/or said local control unit; - calculating statistics information based on said condition information and/or performance information at said local control unit; - buffering said condition information and/or performance information and/or statistics information at said local control unit; - transmitting said condition information and/or performance information and/or statistics information to said remote monitoring unit, at predetermined and/or adaptive time intervals; - processing said condition information and/or performance information and/or statistics information at said remote monitoring unit as being included in a cloud computing architecture, for establishing a service need condition and to provide an image of the at least one transportation device in the system, wherein diagnosis and prognosis algorithms are applied to generate a service need report if a problem is predicted to likely occur soon, wherein parts of diagnosis and prognosis are distributed to a data analysis platform and a maintenance unit located at different computers in the cloud, wherein daily statistics data are sent to the data analysis platform which in turn generates trend information to detect a decreasing or increasing trend and a maintenance action is triggered before failure of the transportation device or any part of it takes place, which would prevent transportation operation; and - transmitting said service need condition selectively to the local control unit and/or a mobile service unit. - detecting raw data connected to said at least one function at said control board and/or said local control unit; - generating condition information and/or performance information based on said raw data at said control board and/or said local control unit; - calculating statistics information based on said condition information and/or performance information at said local control unit; - buffering said condition information and/or performance information and/or statistics information at said local control unit; - transmitting said condition information and/or performance information and/or statistics information to said remote monitoring unit, at predetermined and/or adaptive time intervals; - processing said condition information and/or performance information and/or statistics information at said remote monitoring unit as being included in a cloud computing architecture, for establishing a service need condition and to provide an image of the at least one transportation device in the system, wherein diagnosis and prognosis algorithms are applied to generate a service need report if a problem is predicted to likely occur soon, wherein parts of diagnosis and prognosis are distributed to a data analysis platform and a maintenance unit located at different computers in the cloud, wherein daily statistics data are sent to the data analysis platform which in turn generates trend information to detect a decreasing or increasing trend and a maintenance action is triggered before failure of the transportation device or any part of it takes place, which would prevent transportation operation; and - transmitting said service need condition selectively to the local control unit and/or a mobile service unit.