EXPERT AAN HET WOORD“ON THE ROAD TO INTELLIGENT PROCESSING”

dr. ir. Edwin Zondervan, professor - TU Eindhoven

Seminar Smart Industry | 11 november 2015 | Pagina 1

EDWIN ZONDERVAN

On the road to intelligent processing

2

Outline

ForecastGoogle maps/TomTom

This is food for further thought!What is the process industry?

Let’s get a picture of what is processing and what process engineers do in their work?

What is processing intelligence? A lot of scientific progress is done to do processing more intelligently,

but I have a certain definition of “processing intelligently” ExamplesCommon denominatorChallengesOutlook

3

Forecast

This presentation is the development of a “vision in progress”

Intelligent or smart processing start with taking “smart decisions”

The development of tools for decision-making is key!

One possible direction is: network modeling. (Many process engineering problems can be viewed as networked problems, and solved accordingly).

4

Google maps/TomTom

To get here today, I used google maps and/or my GPS navigation… these tools brought me efficiently from A to B.

Some observations:

1. Big Data: Large database with information that can be efficiently searched

2. Adaptive; adjust to uncertainties

3. Alternatives (fastest, calmest, most touristic, …)

4. Algorithm in place to solve network problem

5

What is “processing”?

…Chemical and mechanical conversion of raw materials into products.

…common in the food, beverage, chemical, pharmaceutical, consumer packaged goods, and biotechnology industries, the relevant factors are the ingredients, not parts; formulas, not bills of materials; bulk materials rather than individual units

6

Example of a Process flow diagram

Typical processing equipment: Reactors, separators, pumps, heat exchangers, …

7

How do we process “intelligently”?

Look at the process technology department of TU/e, research & development in: multi-scale multi-phase flow, transport phenomena, integrated and intensified reactors, catalysis, new (reactive) separations and affinity solvents, and renewable feedstock conversion.

8

What is “smart processing”?

Dramatically intensified application of networked intelligence through the complete processing supply chain*

leading to: severe business transformations towards demand-

dynamic economics, performance base enterprises, demand-driven supply chains and a broad based workforce (involvements & innovation)

*After J. Davis et al. (2012)

9

Decision-making is key

My believe is that the essence is on “smart” decision-making: How to design and operate processing systems in such

way that objectives are meet.

Definition: PSE (process systems engineering) is concerned with the systematic analysis and optimization of decision making processes for the discovery, design, manufacture and distribution of chemical products.

10

Examples: Reactor

Performance:SafetyQualityEconomicsEnvironmental…

Degrees-of-freedomDesign and operational parameters, e.g. geometryStirringTemperature,Pressure

A

B

C

A

B

C

A

B

C

Different options, many combinations

possible…

A

B

C

A

B

C

A

B

C

A

B C

A

B

C

A

B

CA

B

C

A

B

C

A

B

Ctim

e = even more combinationsOutcomes: Optimal operational strategy to switch efficiently (50%) from one product to another,

see Reche et al. (2013)

11

Examples: Biorefinery design

Biomass (lignocellulos

e)Variation in composition

and flow

A

B

C

A

B

C

A

B

C

A

B

C Product portfolioDifferent products (ethanol,

buthanol, …)

Raw material Product

Different processing options, many

combinations possible

Pretreatment FermentationDownstream Downstream

Outcomes: Tool for the generation and selection of different refinery designs, balancing of different objectives, See Zondervan et al. (2012)

12

Examples: Pharmaceutical separations

ABCD

ABC|D

AB|CD

A|BCD

A|BC

AB|C

BC|D

B|CD

A|B

C|D

B|CMixture of

components with an active

pharmaceutical

component

Different routes to separate components from each

other……Including different operations will lead to more separation

routesOutcomes: tool to effectively screen suitable separation routes from a large set of generated alternatives, novel concept to unite process synthesis with process heuristics, see Morao et al. (2012)

13

Examples: Fast Moving Consumer Good Chains

Ingredients (Milk, sugar,

…, ) from different suppliers

A

B

C

A

B

C

A

B

C

A

B

C Product portfolio

Many SKU’s Different supply chain routes and designs, many

combinations possible

storagepurchase

storage

Market/retailer

processingprocessing

Outcomes: tools to deal with large scale SC’s, significant savings in environmental burden (~10-15%) without affecting the costs and no need for investments van Elzakker et al. (2014)

14

What is the Common denominator?

Uncertainty in sources and sinks (e.g. in demand and supply)

Often multiple, conflicting objectives to satisfy (e.g. economics vs. environment)

Large complex networked decision structures.

Systematic approaches have often lead to significant savings (de Klinkende Munt!)

15

Where lie the challenges?

Uncertainty…designing and operating systems such way that flexibility is ensured

Multiple objectives…designing and operating systems such that the best trade-off between economic and environmental performance is found

Complexity…selecting best options from large set of operating and design modes

16

Outlook

Processing problems could be in essence also defined as network problems;

In our field the skill to “keep overview” is increasingly important;

Maybe we could take inspiration from the internet (adaptive supply chains such as amazon, search engines, route planners) to tackle our network problems?;

17

EINDE

Seminar Smart Industry | 11 november 2015 | Pagina 18