Processing geometric inputs play a crucial role in the product development cycle. Ever since the introduction of complex algorithm libraries, the NPD landscape has changed drastically, and for good. Typically, a well suitable library streamlines the work process by executing complicated tasks using a wide array of functions.
An algorithm library basically works on the principle where it is fed with specific instructions to execute in a way with functionalities customised with it. For example, in manufacturing industry; there is a term known as point cloud library and it holds its expertise in converting millions of point cloud data into mesh models.
There are particular algorithms to perform numerous perplexing tasks. There are platforms that use specific and unique functionalities and programming to get the job done. Manufacturing requirements, end product objectives lay down the necessities for choosing a particular algorithm library. This article sheds a light on 6 key factors to consider while selecting any algorithm library.
The intersection of AI and 3D printing has long been predicted. AI can analyze a 3D model and determine which parts will fail to form the part. 3D printers can also remove material from failed regions and use AI to create a different version. AI can even analyze a part’s geometry and identify a potential problem so an alternative way to create it can be found. The end result? A better-designed part with a high rate of success.
Once data has been fed and stored, methods for compressing this kind of data become highly interesting. The different algorithm libraries come up with their own set of functionalities. Ideally, functionalities are best when developed by in-house development team, to suit up in accordance with design objectives. It is a good practice to develop functionalities to address complex operations as well as simple tasks. It is also essential to develop functions which might be of need down the line. In the end, one’s objective defines what functionality laced algorithm library will be in use.
Data Size and Performance
A huge data can be challenging to handle and share between project partners. A large data is directly proportional to a large processing time. All the investments in hardware and quality connections will be of little use if one is using poor performing library. An algorithm library that allows for the process of multiple scans simultaneously has to be the primary preference. One should also have a good definition of the performance expectations from the library, depending on your application whether real time or batch mode.
Libraries that automate manual processes often emphasize on processing speed, delivering improvements to either the processing or modeling. This allows for faster innovation and often better, yet singular, products. As witnessed in the case of point cloud, the ability to generate scan trees after a dataset has been processed greatly improves efficiency. A system will smooth interface that permits fast execution, greatly reduces the effort and time taken to handle large datasets.
Make versus Buy
This situation drops in at the starting phases of processing. Let us take an example of point cloud libraries. Some of the big brands producing point cloud processing libraries are Autodesk, Bentley, Trimble, and Faro. However, most of these systems arrive as packages with 3D modelling, thereby driving up costs. If such is the case, it is advisable to form an in-house point cloud library that suits the necessities. Nowadays, many open source platforms give out PCL to get the job done which has proven to be quite beneficial.
The commercial aspect also plays a vital role in while choosing an algorithmic library. Whether to opt for single or recurring payment depends upon the volume and nature of the project.
There are different models to choose from, if one decides to go with licensing a commercial library:
A: Single payment: no per license fees, and an optional AMC
B: Subscription Based: Annual subscription, without per license fees
C: Hybrid: A certain down payment and per license revenue sharing
Whatever option you select, make sure there is a clause in the legal agreement that caps the increase in the charges to a reasonable limit.
Storage, Platforms and Support
Storage has become less of an issue than what it was even a decade ago. Desktops and laptops with more than a terabyte of capacity are all over the market. Not every algorithm library requires heavy graphics. Investing in a quality graphics card is only important if your preferred library demands heavy graphic usage. That doesn’t mean investing in cheap hardware and storage systems available. A quality processor with lot of RAM is decent if the processing task is CPU and memory intensive. Another point to look into, is the type of platform or interface to be exact, the algorithm library supports. Varied requirements call for varied platforms such as Microsoft, Mac, and Linux. The usage, and licensing should be taken into account before selecting an interface.
Last but not the least, it is to mention that the inputs from customers are highly significant and there has to be a robust support system to address any grievance from the customer side. Having a trained support staff or a customized automated support system must be given high priority.