This invention relates to a process, system and computer code to sequence processes to automate based on return on investment or ROI. The process and system divides considers the mix of human and robotic steps to optimize cost, quality and cycle-time of the process; classifying a process based on an entity and corresponding divisional partition, such as one of a group, department or stakeholder, and (2) generating key criteria; categorizing the ROI; applying constraints such as one of (a) cost, (b) quality or cycle-time; comparing one of (a) the human entered data, (b) the robot entered data, (c) the bot acquired data, with respect to one (i) cost, (ii) quality or (iii) cycle-time; queuing one of (a) a human task, (b) a robot task, or (c) a bot constructed task; storing one of (a) tracking process changes, (b process details and constraints in the event of a change.

Systems methods for computer-aided machining includes A) providing a material batch with an undetermined machinability to a machining tool, B) specifying a set of machining conditions having a machining speed, C) inserting a tool that has a predetermined type and a predetermined wear into the machining tool, D) machining the material batch with the machining tool, monitoring wear of the inserted tool during the machining, and determining a first tool life of the tool, E) repeating Steps B, C and D to determine a second tool life, while setting a different machining speed in Step B and inserting a tool of the same type in Step C, F) determining coefficients of a model associated with the material batch, based on the machining speed, the different machining speed, the first and the second tool life, and G) determining machinability of the material batch based on the model.

Systems methods for computer-aided machining includes A) providing a material batch with an undetermined machinability to a machining tool, B) specifying a set of machining conditions having a machining speed, C) inserting a tool that has a predetermined type and a predetermined wear into the machining tool, D) machining the material batch with the machining tool, monitoring wear of the inserted tool during the machining, and determining a first tool life of the tool, E) repeating Steps B, C and D to determine a second tool life, while setting a different machining speed in Step B and inserting a tool of the same type in Step C, F) determining coefficients of a model associated with the material batch, based on the machining speed, the different machining speed, the first and the second tool life, and G) determining machinability of the material batch based on the model.

A production system between processes is automatically determined using work performance data acquired at a production site, and a process model in which a flow shop and a job shop are mixed is automatically generated. A process model automatic generation system 210 reads work performance data from work performance data 120 and extracts a process flow for each product (130). Next, a synthesis flow obtained by combining a plurality of process flows is created, and a production system between processes corresponding to a closed path is changed to a job shop to automatically determine a production system (140). Finally, a process model in which a flow shop and a job shop are mixed is generated (150) and displayed on a display screen 160.