3m Innovative Properties Company

Solventum Intellectual Properties Company

Frederick J Arsenault

Brian E Brooks

Gilles J Benoit

Tyler W Olson

Peter O Olson

Nicholas A Johnson

Himanshu Nayar

John Allen Wheatley

Catherine A Leatherdale

Aaron K Nienaber

Jon A Kirschhoffer

Glenn E Casner

Maureen Ann Kavanagh

Steven P Floeder

Jonathan B Arthur

Brandon Alan Bartling

Brett R Hemes

Thomas J Strey

Nathan J Herbst

Don Vincent West

Christopher M Brown

Patrick G Zimmerman

Mark W Orlando

Timothy J Clemens

Jeffrey P Adolf

Lori A Sjolund

Andreas Backes

Vincent J Laraia

Gregory P Moriarty

Peter J Schneider

Sarah M Mullins

Cory D Sauer

Carter C Hughes

Miaoding Dai

Zachary M Schaeffer

Susan L Woulfe

Scott L Barnett

Vincent Jl Chevrier

Mark A Tomai

A method of performing a process using a plurality of control signals and resulting in a plurality of measurable outcomes is described. The method includes optimizing the plurality of control signals by at least: receiving a plurality of process constraints; receiving, for each measurable outcome, an optimum range; receiving, for each control signal, a plurality of potential optimum values; iteratively performing the process, where for each process iteration, the value of each control signal is selected from among the plurality of potential optimum values received for the control signal; for each process iteration, measuring each outcome in the plurality of measurable outcomes; and generating confidence intervals for the control signals to determine a causal relationship between the control signals and the measurable outcomes. The method includes performing the process using at least the control signals determined by the causal relationship to causally affect at least one of the measurable outcomes.

Method of performing a process and optimizing control signals used in the process

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for optimizing a process of polishing semiconductor wafers. In one aspect, the method comprises repeatedly performing the following: i) selecting a configuration of input settings for polishing a semiconductor wafer, based on a causal model that measures current causal relationships between input settings and a quality of semiconductor wafers; ii) receiving a measure of the quality of the semiconductor wafer polished with the configuration of input settings; and iii) adjusting, based on the measure of the quality of the semiconductor wafer polished with the configuration of input settings, the causal model.

Polishing semiconductor wafers using causal models

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for determining causal models for controlling environments. One of the methods includes repeatedly selecting control settings for the environment based on (i) a causal model that identifies causal relationships between possible settings for controllable elements in the environment and environment responses that reflect a performance of the control system in controlling the environment and (ii) current values of a set of internal parameters; and during the repeatedly selecting: monitoring environment responses to the selected control settings; determining, based on the environment responses, an indication that one or more properties of the environment have changed; and in response, modifying the current values of one or more of the internal parameters.

Determining causal models for controlling environments

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for determining causal models for controlling environments. One of the methods includes identifying a procedural instance; selecting control settings for the procedural instance, comprising, for a particular one of the controllable elements: assigning the procedural instance to a cluster for the particular controllable element in accordance with current values of a set of clustering parameters for the particular controllable element; and selecting a setting for the particular controllable element for the procedural instances based on a causal model that is specific to the cluster; obtaining environment responses to the selected control settings that define a value of the performance metric for the procedural instance; and updating, for the particular controllable element, the causal model for the cluster for the controllable element to which the procedural instance was assigned based on the value of the performance metric.

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for optimizing a manufacturing process. In one aspect, the method comprises repeatedly performing the following: i) selecting a configuration of control settings for a manufacturing process, based on a causal model that measures causal relationships between control settings and a measure of a success of the manufacturing process; ii) determining the measure of the success of the manufacturing process using the configuration of control settings; and iii) adjusting, based on the measure of the success of the manufacturing process using the configuration of control settings, the causal model.

Controlling a manufacturing process using causal models

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for determining causal models for controlling environments. One of the methods includes identifying a procedural instance; determining a temporal extent for the procedural instance based on temporal extent parameters for the one or more entities in the procedural instance; selecting control settings for the procedural instance; monitoring environment responses to the control settings that are received for the one or more entities; determining which of the environment responses to attribute to the procedural instance in a causal model; and adjusting, based at least in part on the environment responses that are attributed to the procedural instance, the temporal extent parameters for the one or more entities.

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for determining causal models for controlling environments. One of the methods includes repeatedly selecting, by a control system for the environment, control settings for the environment based on internal parameters of the control system, wherein: at least some of the control settings for the environment are selected based on a causal model, and the internal parameters include a first set of internal parameters that define a number of previously received performance metric values that are used to generate the causal model for a particular controllable element; obtaining, for each selected control setting, a performance metric value; determining that generating the causal model for the at particular controllable element would result in higher system performance; and adjusting, based on the determining, the first set of internal parameters.

A method of optimizing a plurality of control signals used in operating a vehicle is described. The operation has a plurality of associated measurable parameters. The method includes: for each control signal, selecting a plurality of potential optimum values from a predetermined set; operating the vehicle in at least a first sequence of operation iterations, where for each pair of sequential first and second operation iterations in the first sequence of operation iterations, the potential optimum value of one control signal in the first operation iteration is replaced in the second operation iteration with a next potential optimum value of the control signal, while the potential optimum values of the remaining control signals are maintained; for each operation iteration, measuring each parameter in the plurality of measurable parameters; and generating confidence intervals for the control signals to determine causal relationships between the control signals and the measurable parameters.

Method of optimizing control signals used in operating vehicle

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for determining causal models for controlling environments. One of the methods includes obtaining data specifying baseline probability distributions for each of a plurality of controllable elements; maintaining a causal model; repeatedly performing the following: selecting control settings for the environment based on the causal model and values for a particular internal parameter of the control system that are sampled from a range of possible values; selecting control settings for the environment based on the baseline probability distributions; monitoring environment responses to the control settings selected based on the causal model and the control settings selected based on the baseline probability distributions; determining, for each of the possible values, a measure of a difference between a current system performance and a baseline system performance; and updating how frequently each of the possible values is sampled.

Systems and methods for organizing and controlling the display of content, then measuring the effectiveness of that content in modifying behavior, within a particular temporal and spatial dimension, so as to minimize or eliminate confounding effects.

Systems and methods for spatial and temporal experimentation on content effectiveness

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for optimizing a process of manufacturing a product. In one aspect, the method comprises repeatedly performing the following: i) selecting a configuration of input settings for manufacturing a product, based on a causal model that measures causal relationships between input settings and a measure of a quality of the product; ii) determining the measure of the quality of the product manufactured using the configuration of input settings; and iii) adjusting, based on the measure of the quality of the product manufactured using the configuration of input settings, the causal model.

Manufacturing a product using causal models

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for optimizing a process of manufacturing a biologic pharmaceutical. In one aspect, the method comprises repeatedly performing the following: i) selecting a configuration of input settings for manufacturing a batch of a biologic pharmaceutical based on a causal model that measures current causal relationships between input settings and a measure of a quality of batches of the biological pharmaceutical; ii) determining a measure of the quality of a batch of the biological pharmaceutical manufactured using the configuration of input settings; and iii) adjusting, based on the measure of the quality of the batch of the biological pharmaceutical, the causal model.

Manufacturing a biologic pharmaceutical using causal models

Method for active battery management to optimize battery performance. The method includes providing signal injections for charging and discharging of a battery. The signal injections include various charging and discharging profiles, rates, and endpoints. Response signals corresponding with the signal injections are received, and a utility of those signals is measured. Based upon the utility of the response signals, data relating to charging and discharging of the battery is modified to optimize battery performance and to determine when to discharge the battery into a power grid in order to return power to the grid in exchange for an economic benefit such as a payment or rebate from a utility company.

Active battery management method for economic optimization

Systems and methods for organizing and controlling the display of content, then measuring the effectiveness of that content in modifying behavior, within a particular temporal and special dimension, so as to minimize or eliminate confounding effects.

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Stillwater, MN, United States of America

Frederick J Arsenault