Abstract: A method, computer system, and a computer program product for lifecycle prediction is provided. The present invention may include identifying a unit of a product that has been selected from a store bin. The present invention may include retrieving data from at least one connected Internet of Things (IoT) device and a connected infrared scanner. The present invention may include predicting a lifecycle of the identified unit. The present invention may include displaying the lifecycle on the at least one connected IoT device or the infrared scanner. The present invention may include determining whether the unit is added to a cart. The present invention may lastly include pushing the collected data to a point of sale for generating data at checkout.

Abstract: A method, computer system, and a computer program product for lifecycle prediction is provided. The present invention may include identifying a unit of a product that has been selected from a store bin. The present invention may include retrieving data from at least one connected Internet of Things (IoT) device and a connected infrared scanner. The present invention may include predicting a lifecycle of the identified unit. The present invention may include displaying the lifecycle on the at least one connected IoT device or the infrared scanner. The present invention may include determining whether the unit is added to a cart. The present invention may lastly include pushing the collected data to a point of sale for generating data at checkout.

Abstract: Disclosed herein is a method for selecting a material that most closely matches a desired set of properties, the method comprising: obtaining at least one input parameter from a user; retrieving actual property values for at least one preliminary matching material from a global data repository; determining a match between each preliminary matching material matches and a desired set of property values; and outputting the results to the user.

Abstract: Material selection systems and methods for quickly identifying which existing material best matches a desired set of properties are described so that product development time can be minimized. Users may input the properties they desire in a material, which properties they want searched and scored, the acceptable values of those properties, and a priority value for each property. Preliminary matching materials may be retrieved from a materials database, and an index value for each property value may be calculated. One of four fuzzy membership functions may then be utilized to calculate a scored property value for each property of each material. The scored property value may then be weighted to account for the priority value assigned to each property. The results may then be sorted in descending order based on their overall match scores, and output to the user so the best matching material(s) is readily identifiable by the user.

Abstract: Material selection systems and methods for quickly identifying which existing material best matches a desired set of properties are described so that product development time can be minimized. Users may input the properties they desire in a material, which properties they want searched and scored, the acceptable values of those properties, and a priority value for each property. Preliminary matching materials may be retrieved from a materials database, and an index value for each property value may be calculated. One of four fuzzy membership functions may then be utilized to calculate a scored property value for each property of each material. The scored property value may then be weighted to account for the priority value assigned to each property. The results may then be sorted in descending order based on their overall match scores, and output to the user so the best matching material(s) is readily identifiable by the user.