Abstract: A system may include a vehicle. The vehicle may include an array of haptic devices. The system may further include at least one processor configured to: determine a location of an object or occurrence relative to the user; based at least on the location of the object or occurrence relative to the user, select at least one haptic device of the array of haptic devices to be driven and function as a directional haptic alert to the user, wherein the directional haptic alert is indicative of a direction from the user toward the object or occurrence; and output at least one command to cause a driving of the selected at least one haptic device, wherein the driving of the selected at least one haptic device is perceivable by the user as the directional haptic alert.

Abstract: Methods, systems and apparatus, including computer programs encoded on computer storage medium, for controlling operations of machine tool workstations. Machine tool workstations are grouped into functional groups. Neural networks corresponding to the functional groups are trained to process respective inputs representing parts to be processed to generate respective outputs representing sequences of ordered subsets of the parts that produce a reduced setup time for workstations in the functional groups. Data representing respective collections of parts to be processed by workstations included in the functional groups is processed using the trained neural networks to generate corresponding sequences of ordered subsets of the collection of parts. Average delay times associated with the generated sequences of ordered subsets of the collection of parts are computed.

Abstract: Methods, systems and apparatus, including computer programs encoded on computer storage medium, for processing multiple jobs using a plurality of workstations. The plurality of workstations are grouped into multiple Pull groups, each Pull group including one or more workstations of a same type. The processing includes, repeatedly, at each of multiple time steps until a predetermined condition is satisfied: collecting, using sensors that monitor the plurality of workstations, sensor data from Pull groups in the multiple Pull groups; computing, for each of the multiple jobs, a current remaining lead time using the collected sensor data and Little's Law; and adjusting, based on the computed current remaining lead times, priorities at which the multiple jobs are processed by each Pull group.

Abstract: Methods, systems and apparatus, including computer programs encoded on computer storage medium, for controlling operations of machine tool workstations. Machine tool workstations are grouped into functional groups. Neural networks corresponding to the functional groups are trained to process respective inputs representing parts to be processed to generate respective outputs representing sequences of ordered subsets of the parts that produce a reduced setup time for workstations in the functional groups. Data representing respective collections of parts to be processed by workstations included in the functional groups is processed using the trained neural networks to generate corresponding sequences of ordered subsets of the collection of parts. Average delay times associated with the generated sequences of ordered subsets of the collection of parts are computed.

Abstract: Methods and systems for generating sensor data, wherein the sensor data includes measured transit time information for items flowing through a work process, accessing a set of control data for one or more machine tool workstations and accounting data for the work process, calculating a standard deviation of the measured transit time information, calculating an achievable minimum WIP for at least one of the workstations using current values of workstation performance parameters, receiving input including: information identifying process improvement projects and corresponding predictive performance parameter values, and information identifying resources available for process improvement, for the at least one of the workstations: determining an achievable minimum WIP using the corresponding predictive performance parameter values, determining a reduction in minimum WIP based on the difference between the achievable minimum WIP for the current performance parameter values and the predictive performance parameter

Abstract: Predictive cost reduction based on a thermodynamic model, in which parameters associated with a process are accessed. The parameters include a quantity of units of work-in-process at first and second times, and first and second constants respectively indicative of growth between the first and second times, and of a translated reduction of the work-in-process to a reduction of cost. A thermodynamic model is applied to the accessed parameters, and a predictive cost reduction associated with an improvement of the process based on applying the thermodynamic model is output.

Abstract: Predictive cost reduction based on a thermodynamic model, in which parameters associated with a process are accessed. The parameters include a quantity of units of work-in-process at first and second times, and first and second constants respectively indicative of growth between the first and second times, and of a translated reduction of the work-in-process to a reduction of cost. A thermodynamic model is applied to the accessed parameters, and a predictive cost reduction associated with an improvement of the process based on applying the thermodynamic model is output.

Abstract: A method for measuring and reducing the cost of complexity in producing products or providing a service by comparing selected non-value added steps in the manufacturing or service process with the number of different products or services provided, so as to provide the non-value added cost of the product or service for various selected complexities. The number of products required to be processed or held in inventory for a particular demand, or the number of different specific services required for a particular demand of the service is determined by comparing the number of different product part numbers, or service categories offered, with selected non-value added steps in the respective processes. Mathematical analyses are derived from equations of motion of process improvement including the first derivative of process velocity.

Abstract: A method for measuring and reducing the cost of complexity in producing products or providing a service by comparing selected non-value added steps in the manufacturing or service process with the number of different products or services provided, so as to provide the non-value added cost of the product or service for various selected complexities. The number of products required to be processed or held in inventory for a particular demand, or the number of different specific services required for a particular demand of the service is determined by comparing the number of different product part numbers, or service categories offered, with selected non-value added steps in the respective processes. Mathematical analyses are derived from equations of motion of process improvement including the first derivative of process velocity.

Abstract: The invention determines the batch size of materials required for each process within a workstation based on a given shipment schedule, as well as the values of several other workstation variables that are determinative of workstation and factory performance. With this information, the user of the invention may schedule production for the factory or spot and prioritize workstations requiring the most improvement, and determine the character and quantity of improvement.