cfransman@predikto.com

About Carl Fransman

Carl Fransman comes to Predikto from MCA Solutions where he was Managing Director for EMEA. Mr. Fransman has over 25 years of international management experience in high technology industries. While there, he built key account relationships and partnerships, hired EMEA staff and spearheaded the company's international expansion. Mr. Fransman also holds a number of board mandates in technology companies and in the non-profit sector. His previous experience includes management roles in technology and in the manufacturing sector. Mr. Fransman is based in Belgium and joined Predikto in 2015 to lead its international expansion in the EMEA region. He is fluent in Dutch, French, English and conversant in German and Spanish, and has an industrial engineering degree from the University of Leuven and an MBA with high honors from Solvay Business School in Brussels.
404/2016

What’s happening to my train (and by extension, any equipment)?

By |April 4th, 2016|Categories: Uncategorized|

At regular intervals, company managers are asked to provide their forecast for the next period(s). While some dread this exercise – and it is a tough ask for them to put together this forecast – others can almost pull the numbers on request. Why? Because they have good visibility on current and past performance, on current and past conditions and are well informed on forecasted evolutions in the market. Why is that so difficult for […]

1403/2016

Industry 4.0 in a nutshell

By |March 14th, 2016|Categories: Uncategorized|

In a nutshell? It’s not about the machines! It’s about what ties them together.
The whole Industry 4.0 movement is drawing a lot of attention – and rightly so! Business leaders and policy makers alike underline the importance of the fourth industrial revolution to maintain some sort of a balance in a globally competing world. While for some businesses it makes perfect sense to compete on price alone, for others the focus on value (functionality, form […]

303/2016

Maintenance optimization goals

By |March 3rd, 2016|Categories: Uncategorized|

When asked about optimising maintenance, different angles can be explored.
First, maintenance optimization can target the outcome; i.e. better maintenance. Better maintenance should result in less failures between maintenance intervals. Additionally, better maintenance can target lower costs for the same outcome. Business process optimization is the usual approach to achieving these targets.

Today, I’d like to highlight two aspects of maintenance optimization that are at the heart of predictive analytics projects for maintenance. The first, and typically […]

2602/2016

Part removal economics

By |February 26th, 2016|Categories: Uncategorized|

You just installed the latest and greatest in predictive analytics and out come the first results. Now what?
Interpretation of the forecast is key. First and foremost it is crucial to understand that no two forecasts mean the same. Let’s take a couple of examples to see how specific forecasts could mean very different things to your operations. Parts A and B are both forecasted to fail with a equal likelihood over the next two weeks. […]

1502/2016

To wait or not to wait, that’s the question

By |February 15th, 2016|Categories: Uncategorized|

With everybody talking about predictive analytics, what should I do as manager of an aftermarket division?
Before launching any project, one should carefully evaluate one’s current and projected future position with regards to aftermarket services; are these critical to your competitive offering or not? Some companies choose to sell their goods and leave aftermarket services to third parties – i.e. the traditional automotive business model. Fair enough although even traditional approaches get challenged regularly – either […]

802/2016

Life Expectancy of an Algorithm

By |February 8th, 2016|Categories: Predictive Analytics|

In our field of predictive analytics (asset health and failures), and I presume the same goes for other fields, there is a major misconception about what an algorithm represents. Speaking with business leaders and, more worryingly, practitioners too, about PdA and in most cases the conversation will turn to “and then we build the algorithm that describes the behaviour of…” Here’s some bad news for these people; many, if not most, assets can’t be described […]

202/2016

Why do we need so much data?

By |February 2nd, 2016|Categories: Predictive Analytics|

Most of us remember the double slit experiment from our physics classes. For those who don’t, here’s a (very) short reminder: a light is shone through two fine slits and the resulting image is proof of the dual nature of light.
If that experiment is done with an emitter that can send single particles of light and the receptor is a photo-sensitive surface, an interesting phenomenon occurs; ‘looking at’ the receptor too soon (if it’s a photo […]

2601/2016

Help, my data’s all over the place!

By |January 26th, 2016|Categories: Uncategorized|

One of the main problems with any corporate IT project is getting all the data to the system. Data is generated in a multitude of systems and stored in just as many places and formats. Some data gets duplicated and/or transformed before stored in other systems. Rarely do even corporate IT departments know what is stored, where and in what format. Sometimes data is stored and nobody seems to know what it means… 
I visited a […]

2201/2016

What do you mean, no spare?

By |January 22nd, 2016|Categories: Predictive Analytics|

Forecasting is only useful if the result is applicable… and to the point! I may have perfectly forecasted the weather but if I’m going to spend the whole day inside, this has no impact on me. This is the same with industrial applications. Current interest in predictive analytics results in plenty of pilot projects of which most focus on how well the forecast performs. To the non-initiated this means; out of every 100 failures, did […]

1101/2016

The many faces of maintenance

By |January 11th, 2016|Categories: Uncategorized|

When referring to maintenance, people often forget to distinguish between different kinds of maintenance. Yet, correctly separating each kind is a pre-requisity for a well-managed business.

The first kind of maintenance is one we all know from taking our cars to the garage for a time- (i.e. annual) or distance-(i.e. every 10,000 miles) based check. During these routine maintenance, several parts, such as oil filters or brake pads, are being replaced as part of a preventive […]