Overview

PIAnO(Process Integration, Automation and Optimization)
Derives the optimum design solution for a product based on a given dataset or real time engineering data from simulations.
This maximizes the value of the product by improving the product quality and performance while reducing the design cost of the development process.

PIAnO started out as a software for process integration and design optimization, and for more than 15 years it has provided customers with a clear value of design optimization. Now faced with a new era of data, PIAnO has taken the next step to engineering data based design optimization.
To push forward, we are developing various decision making tools based on our AI platform, Bruce.

PIAnO can be used for any field in engineering that can provide the appropriate data.
It will continue to grant innovation for not only product and process design but also any where decision making is required for optimal parameters.

ㅡ Get a PIAnO Brochure ㅡ

Features

PIAnO consists of four independent applications which allows users the optimal accessibility and usability for their task where applications can also systematically link with each other creating tremendous synergy.

The most common use for Composer is composing an Analysis Task to generate an automated simulation process, apply various Design Tasks for design optimization, and analyze results using Reviewer. Simple and clear workflow will increase productivity as well as prevent users from stress and making mistakes.

A simple but flexible tool for integrating and automating simulation processes from external s/w is provided using files and batch commands. Data can be selected from input and output files through the UI for each step. Additionally, we support Python, VBScript, JScript, Excel, Matlab, etc. exclusive interfaces.

PIAnO supports cost efficient algorithms for finding an optimal design of problems involving high cost simulation data; STDQAO uses sensitivity information for metamodel generation and sequential approximate optimization, PQRSM is a sequential approximate optimization algorithm based on a specific DOE. ePPAO uses polynomial based sequential approximate optimization where the maximum number of simulations can be defined. FSolver is specialized to find a feasible solution over optimal.

PIAnO supports methods for uncertainty considered design optimization; an efficient method for uncertainty estimation, enhanced dimension reduction (eDR), and probabilistic sensitivity analysis (PSA). Conventional methods such as MCS, LHS, and FORM are also supported where each method can be used for relevant purposes.

Sampler is a standalone application for design of experiments. It supports not only the conventional methods but also particular space-filling methods. It also includes a tool that automatically selects the most appropriate sampling method for the given problem. For orthogonal arrays, candidates are presented based on the number of factors and levels. Convenient tools for removing duplicates, changing the range for variables, and visualizing the samples are also included.

Metamodeler is a standalone application for metamodeling.
It includes various methods from both conventional and state -of-the-art machine learning models. BruceMentor, developed on our AI platform (Bruce), can automatically select the most appropriate metamodel for the given data. Metamodeler also provides tools for handling duplicates and outliers, visualization of the built metamodels, and evaluate its performance. A built model can be exported as an excel spreadsheet or an independent executable.

Reviewer is a standalone application for analyzing the results obtained from Composer using features appropriate for specific tasks. Reviewer can be used to explore and visualize the design space for design optimization using the given data or for screening out globally insignificant variables using the AI based smart screening tool.

Effects

Widely used for improving industrial product development QCD as well as design flexibility

Quality▲

Quality Enhancement considering various design requirements

Cost▼

Cost Reduction employing optimization technologies

Delivery▼

Delivery Time Reduction using a process integration and automation

Flexibility▲

Increased Design Flexibility providing a customized design solution

Applications

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