Process Intensification: A Prerequisite for Success in Custom Manufacturing - Chemspec 2016, Basel Dr. Christoph Schaffrath Dr. Guido Giffels ...
←
→
Page content transcription
If your browser does not render page correctly, please read the page content below
Process Intensification:
A Prerequisite for Success
in Custom Manufacturing
Chemspec 2016, Basel
Dr. Christoph Schaffrath
Dr. Guido Giffels
Slide 1 June 1st, 2016
Saltigo
Who are we and where do we come from?
A globally operating company for exclusive synthesis and innovative fine chemicals
Saltigo profile
customers: ca. 150
Core competence employees: ca. 1.250
products/projects: ca. 400
Since 2006
Market-orientated, 10 production plants
Saltigo – a company custom manufacturing Leverkusen + Dormagen (Ger)
of the LANXESS
group service provider
Lanxess profile
2005-2006 spin off from Bayer 2004
Business Unit Outsourcing partner employees: 16,225
Fine Chemicals for fine chemicals sales: € 7.9 billion in 2015
of LANXESS global footprint: 29 countries
52 production sites
Chemspec Basel 2016, Saltigo Presentation Slide 2 June 1st, 2016
Saltigo – A global player in custom manufacturing serving
different industries
Exclusive production 100 - 5.000 kg/a
Intermediates and APIs
Pharmaceuticals
Regulated area (CGMP, etc.)
Custom Manufacturing
Production volumes > 1.000 t/a
Agro chemicals Intermediates and AIs
Regulated area (Biocides Regulation, etc.)
Often non-exclusive products
Fine chemicals ISO-production or special demands
Chemspec Basel 2016, Saltigo Presentation Slide 3 June 1st, 2016
Focus on market oriented services:
Support of customer needs along the complete project lifecycle
Advanced
Raw Material Active Substance Formulation Customer
Intermediate
Process
Idea Lab Pilotation Production Market
development
Core competence of Saltigo
Custom manufacturing/synthesis up to 5,000 t/a Custom-made process development
Enhanced service support (registration, analytics, etc.) Efficient project management
Professional procurement, reliable supply chain Continuous improvement process
Process Intensification: A prerequisite for successful custom manufacturing
Chemspec Basel 2016, Saltigo Presentation Slide 4 June 1st, 2016
Process intensifications drive efficiency and cost optimization
A diverse toolbox is required for a successful implementation
Project Management
Debottlenecking Data Generation
Capacity Innovation
Process
Plants
Development
Continuous Process Teams
Process Intensification Mindset
Improvement Customer
Technology Analytics
Economy QA and QC
Investments
Milestones and Implementation
Chemspec Basel 2016, Saltigo Presentation Slide 5 June 1st, 2016
Process intensifications –
What does it mean?
„Getting More out of Less“
Chemspec Basel 2016, Saltigo Presentation Slide 6 June 1st, 2016
Getting More out of Less –
How?
Ways to achieve this goal
1. More „Right 1st Time“, optimizing process & parameters to improve
product quality, reducing/omitting number of process steps, reworks, …
2. Changing Equipment (Hardware)
improve setup
3. Higher Space-Time-Yields by Process Optimization,
e.g. shortening cycle time, increasing output/batch etc.
Chemspec Basel 2016, Saltigo Presentation Slide 7 June 1st, 2016
Process Intensification
3 Case studies
Increasing the bulk density of an agrochemical product
Case #1
by using multivariate data analysis
Significant increase of production capacity & productivity
Case #2
by stepwise modification of reactor setup
Shortening cycle time of an exothermic reaction
Case #3
by use of an intelligent control factor
Titel /as Folie 8 19.05.2016
Case Study #1
Objective: increase the bulk density of a crystallized product
Case description
Large-scale custom-made product crystallizes in (at least) 2 polymorphorphic modifications
Customer requires Mod. B, a defined purity (specification!) and a high bulk density
Mod. A Mod. B
Crystallizes kinetically controlled („faster“) Thermodynamically more stable,
may be formed out of Mod. A
Gives better & required purity
Required product form by the customer
Mechanically less stable
Gives lower purity if crystallized directly
Grinding during drying leads to low particle size and
to low bulk density Mechanically more stable, larger particle size
Bulk density is crucial, as a certain amount of Gives higher bulk density
product per big bag is asked by the customer
Chemspec Basel 2016, Saltigo Presentation Slide 9 June 1st, 2016
Case Study #1
Objective: increase the bulk density of a crystallized product
Objective: How to get…
• the right modification (Mod. B) ?
• the right purity ?
• a good bulk density ?
… with a mimimum of effort?
„Is this the
best option?“
Crystallize Mod. B directly:
Purity not sufficient
Crystallize A first, isolate & recrystallize, seeding B:
Works, but additional (re)crystallisation (= effort) V Let‘s look
deeper into
this one
Convert Mod. A Mod. B on the dryer
Possible, but drying process gave varying results ?
Chemspec Basel 2016, Saltigo Presentation Slide 10 June 1st, 2016Case Study #1: Multivariate Data Analysis –
Tool to pick the right parameters and values
Drying Process Multivariate Data Analysis –
Thermal impact triggers the modification normalized data showing effect on bulk density
change from Mod. A Mod. B Data Parts 1-2 v03.M11 (OPLS)(BLM ) E10
P80A
Sources of Variation
Drying Process (not automated) gave Colored according to Var ID ($SourceID)
P80B
P81
various results in bulk density Einsatz aus F2929 Inertisieren
Evakuieren Pressure Kühlen Belüften
TrocknenAustragen
Ende R15Y
R60Y
Temperature R85Y
Multivariate Data Analysis „highlighted“ the
0,02
S10
T10
crucial process parameters during drying: 0,01
T60
T61
Pressure (vacuum) – higher pressure in
T80
T81
p[1]
0
the beginning is better
-0,01
Bulk temperature – higher
temperature in the beginning is better -0,02
Energy input
Energy application (by stirrer): -0,03
Charging Drying Cool, areate, discharge
lower is better – grinding!
0
36
73
109
146
189
294
10
10
42
74
106
138
170
205
251
306
367
665
34
0
62
9
47
86
175
Var ID ($MaturityID)
Parameter data from approx. 60 batches
R2X[1] = 0,111
SIMCA 14.1 - 2016-02-18 15:10:14 (UTC+1)
high amplitude = large impact on bulk density
Chemspec Basel 2016, Saltigo Presentation Slide 11 June 1st, 2016Case Study #1: Increase Product Bulk Density
Rationale behind the “right” parameters
Possible „Routes“ Rationale
A-wet A-dry B-dry:
grinding of Mod A during drying
low bulk density
? V
A-wet B-wet B-dry:
formation of stable Mod B first, then drying,
larger particles and higher bulk density
First tempering the wet product at higher pressure („bad“ vacuum) and resulting higher inner temperature
leads to fast change from Mod. A Mod. B = less grinding of mechanically less stable Mod. A, resulting in a better
bulk density after drying.
Chemspec Basel 2016, Saltigo Presentation Slide 12 June 1st, 2016Case Study #1: Increase Product Bulk Density
Results after optimization
Bulk Density before/after Optimization Summary
Relevant process parameters were identified
Histogram of Bulk density by means of multivariate data analysis
25
Significant increase of bulk density was
20 achieved
Requested amount of product per big bag can
15
be filled
Before Optimization Part 1
10 Optimized Part 2
5
0
7 9 1 3 5 7 9 1 3 5 7 9 1 3 5 7 9 1 3 5 7 9 1 3 5 7 9
2
, 2
, 3
, 3
, 3
, 3
, 3
, 4
, 4
, 4
, 4
, 4
, 5
, 5
, 5
, 5
, 5
, 6
, 6
, 6
, 6
, 6
, 7
, 7
, 7
, 7
, 7
,
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
Chemspec Basel 2016, Saltigo Presentation Slide 13 June 1st, 2016Case Study #2:
Increasing Capacity & Productivity by
Optimized Reactor Setup
Chemspec Basel 2016, Saltigo Presentation Slide 14 June 1st, 2016Case Study #2
Increasing capacity & productivity by optimized reactor setup
Case description
Large scale chlorination product (B) was produced in batch mode with limited capacity
(A) reacts to target product (B). (B) reacts further to byproduct (C) in a consecutive reac-tion. To
maximize selectivity, (A) is only partially converted and recycled during workup
Objective: increase capacity / productivity to meet market demand
Cl2 Cl2
A B C
Target Product Bottleneck
Chemspec Basel 2016, Saltigo Presentation Slide 15 June 1st, 2016Case Study #2
Increasing capacity & productivity by optimized reactor setup
Szenario 2): First expansion
Add 2nd distillation unit
Change to continuous operation of distillation: (A)
Unit 1: recycle (A) Unit 2: isolate product (B) (B)
Doubling chlorination unit
Bottleneck
Cl2 Cl2
A B C
continuous
(C)
Chemspec Basel 2016, Saltigo Presentation Slide 16 June 1st, 2016Case Study #2
Increasing capacity & productivity by optimized reactor setup
Szenario 3): Debottlenecking distillation
(A) Bottleneck
Reactor setup as szenario 2, plus …
Improved column for distillation unit 1
(B)
Cl2 Cl2
A B C
continuous
continuous
(C)
Chemspec Basel 2016, Saltigo Presentation Slide 17 June 1st, 2016Case Study #2
Increasing capacity & productivity by optimized reactor setup
Szenario 4): Optimized Use of Chlorination Unit
Chlorination changed from 2 batch reactors to only one CSTR (A)
(continuously stirred tank reactor) with higher throughput
CSTR = broader residence time distribution higher conversion needed for (B)
the same capacity decreased selectivity, higher portion of (C)
Cl2 Cl2
A B C
continuous continuous
(CSTR)
(C)
Chemspec Basel 2016, Saltigo Presentation Slide 18 June 1st, 2016Case Study #2
Increasing capacity & productivity by optimized reactor setup
Summary
Overall, 4 fold increase of production capacity at doubled productivity (!)
Further upsides:
> back integration into raw material via Lanxess production network
> further conversion of byproduct (C) into sales product improves overall efficiency
Chemspec Basel 2016, Saltigo Presentation Slide 19 June 1st, 2016Case Study #3:
Shortening cycle time by intelligent use
of an appropriate control factor
Chemspec Basel 2016, Saltigo Presentation Slide 20 June 1st, 2016Case Study #3
Shortening cycle time by intelligent use of an appropriate control factor
Case description
Grignard reaction of an aryl chloride (Ar-Cl Ar-Mg-Cl)
- sluggish, but highly exothermic
- accumulation of reaction potential must be avoided to prevent runaway reaction
Standard procedure
Magnesium + solvent are charged to the reactor Heat release
Portion of aryl chloride is added
Await start of reaction (exotherm = heat release; sampling)
Further aryl chloride is added continuously over time (fixed rate), Mass of
controlling/entsuring that exothermic reaction continues Ar-Cl added
Objective: How to control the reaction progress intelligently
to allow maximum speed of addition – ?
Rxn start Main Reaction
Time
Adapted from Kryk et. al., see: Organic Process Research & Development, 2007, 11, 1135-1140
Chemspec Basel 2016, Saltigo Presentation Slide 21 June 1st, 2016Case Study #3
Shortening cycle time by intelligent use of an appropriate control factor
Approach for SAFE but FASTER addition rate of reagent Ar-Cl
Key: Accumulation of Ar-Cl must be avoided
Reaction is run in a closed reactor, allowing reaction temperature above boiling point
of the solvent faster reaction initiation and conversion of Ar-Cl Ar-Mg-Cl
Recording of the reactor‘s calorimetric data installed, allowing a real-time heat balance
From calorimetric data, the theoretical maximum reactor pressure in case of hypothetical
immediate spontaneous full conversion (adiabatic increase of p and T) is calculated,
the so called pMTSR (pressure at Maximum Temperature of the Synthesis Reaction)
The pMTSR is a value for the accumulated reaction potential!
Always staying below the maximum allowed pMTSR as lead parameter,
the maximum addition rate of the aryl halide can be applied shorter cycle time
Chemspec Basel 2016, Saltigo Presentation Slide 22 June 1st, 2016Case Study #3
Shortening cycle time by intelligent use of an appropriate control factor
Standard Procedure Optimized Addition based on pMTSR
pMTSR Limit pMTSR Limit
Pressure, Dosage Rate
Pressure, Dosage Rate
pMTSR Target
pMTSR pMTSR
Reactor Pressure
Dosage Rate Ar-Cl
Dosage Rate Ar-Cl
Time Time
Using the appropriate control factor Improved Dos. Time
allows significant cycle time reduction
Initial Dosage Time
Graphics adapted from H. Kryk et. al., HZDR
Chemspec Basel 2016, Saltigo Presentation Slide 23 June 1st, 2016Summary
Take-Home Messages
Successful process intensification requires:
Knowledge Data, Know-How, Competence, Experience, Ideas People
Ressources Equipment, Technology, Budget, Hands and Heads People
Mindset Objectives, Planning, Interdisciplinary Team-Work People
Acknowledgement to the Saltigo Project Teams!
Thank you for your attention!
Chemspec Basel 2016, Saltigo Presentation Slide 24 June 1st, 2016You can also read
