Do you remember how a 5-inch floppy disk looks? And how to use it? It doesn’t seem like so long ago that we used this floppy quite widely. But, as you can see, we have moved forward, and it’s very interesting how we can enable fast ROI for PLM, how to make a quick implementation, updates online, etc. But at the same time, in my opinion, there are problems that exist today and are also related to long processes. The problem is how to keep my product data for a long period of time. I think that this problem will become more urgent over the next 2-3 years. There are two main reasons for this: Data around us is growing very fast. Most of today’s PLM implementations (even if they are 3-5 years long) are still located on corporate “spinning disks”. As storage is becoming cheaper, this problem is getting pushed to a longer queue, since you can increase your operational storage and postpone the problem to a few years from now.
Most of the discussions related to long term data retention were around CAD formats. Indeed, this is an important topic, but I think that the problem is not limited to data formats, and much wider in scope. I have separate issues on four topics and will analyze the options I see possible for solving these problems.
1. Physical Storage
This is probably not a very “PLM-related” problem. How do you physically keep data? Most of today’s examples I’ve seen use a CD/DVD combination to store data. I’m not so sure if this is so good. The main problem is that by copying data onto a DVD, we are removing data. This is really bad. The biggest value of data being able to use it – by putting your data on a DVD, your data will die. The new development of cloud data centers shows a big promise for solving this problem. I think that companies using cloud data centers will benefit from long data retention and therefore resolve the physical storage problem.
2. Data Models
This one is tricky. Product data is quite complex and not sequential. If you backup your mail, the only model you need is a calendar. You can retrieve any data back using your calendar model – sender(s)/year/month/date. This is all you need to know when you want to retrieve your mail. This is not true with product data. Product data has many dependencies that are very complex and span across timelines related to multiple products etc. So, this is a big problem, in my opinion. Even today I cannot say that a data model is stable for most PDM/PLM implementations. It becomes even less stable over a long period of time. The most advanced development in this field is based on the STEP format, but I still consider this issue very challenging.
3. Data Formats
Most of today’s discussions about long data retention are about formats or CAD formats. When we discuss mainly 3D, one of the first questions we ask is how to store our 3D (and non-3D) graphical models for the long-term. Lifecycle of CAD packages is too short. I think most of today’s implementations are focused on 2D and print storages. There is no silver bullet today, in my view. 3D PDF is promising. Private formats (even if they pretend to be according to industry standards and acceptance, such as JT) can solve the problem only partially. Combining a good data model and data format may work. But more promising is granular data storage – this will let us keep the underlining model behind 3D and 2D data.
4. Logical Access
This is a complex term for the simple word “search”. I don’t want to oversimplify, but maybe I’m wrong. At the end of the day, I may need to find data that I saved 30 years ago and examine or reuse it for a particular reason. You can call this simply “searching”, but we need to bring new ideas to this issue – about how to logically retrieve relevant data in the context of a specific problem/issue/task.
And one more thing… There is a certain promise in environment virtualization usage for long term data retention. You can keep your data and your applications together with you computer systems – and you can use a virtual environment to bring your old systems to life. I don’t know why, but this option always reminds me of sci-fi films when humans were frozen and un-frozen after 100-200 years…. Imagine that you start your MS-DOS now to read your document in Word Perfect.
And this topic probably is not be complete if I don’t mention the aging workforce. Not only do we need to keep product data over a long period of time, but we also need to keep data in order for tomorrow’s users “to use data” rather than “decode” data – there’s a big difference.
So, to sum up: I don’t think we have a fundamental solution for this problem. I’ve heard about a few programs such as LOTAR, development done by PDES. Inc; The Siemens announcement of JT approval for long term retention program, and more (sorry if I left something out).
I’d be glad to discuss if you have had experience in this field and what’s your opinion on how to solve this fundamental issue.