Papermaking 4.0 Using the Internet of Things

Transcription

1 Papermaking 4.0 Using the Internet of Things , DTIP Bled, Dr.Chr.Naydowski 1

2 Papermaking 4.0 applies novel Information Technologies to papermaking.

3 Future OEE > 90% stable

4 Competitiveness Stable means to sustain a gain Time

5 ComCore is designed to integrate data from any source. Why is data networking beneficial for future paper and board manufacturing?

6 Today. Arbitrary fluctuations lead to fluctuating quality and avoid KPI target achievement. Former dewatering Retention Formation target corridor 7 weeks Strength Porosity Case Study, Gap Former, Newsprint, 47 gsm, 350,000 tpa (2013)

7 Paper strength (Stiffness) SCT CD (kn/m) CMT (N) Why do papermakers struggle to keep strength variations within the target corridor for packaging paper? Case study, Gap Former, Testliner and Medium, 100 gsm, 380,000 tpa (2013) Target Corridor Set point for operator guaranteed value Measurement points ( ) Target Corridor x 10 4 Set point for operator guaranteed value Measurement points ( ) 16 months production x 10 4

8 CMT (N) Fear to miss KPI. Overdosing of starch. Needlessly. Testliner Feasibility Study (2013, Germany, 380,000 tpa). Current behavior target corridor excess starch utilization area Strength fluctuations are compensated by excess starch dosage Angst cost (2 /ton) out of specification area SCT CD (kn/m) reached 01/ 12 05/ 13 for CM of 100 g/m 2 specified guaranteed value specified typical value

9 The most overlooked reason for process fluctuations Limited Tools for Decision-making Humans are not able to continuously determine in real-time best action for overall process efficiency such as stability, quality, and cost. => Too much data & not enough relevant information

10 The revolutionary is: data management. The revolutionary result is: a novel level of performance

11 Chapter Divider with Example Image, Arial 40 pt Voith Blue

12 The IoT is the enabler to move process automation: from singular matrix levels into a cyber physical system Company Mgmt Level Production Mgmt Level Process Mgmt Level Control Level Field Level Real time critical 3.X Automation Pyramid Data management in a cloud. Any allocated device contains an IP address

13 VOITH Digital solutions Data based pattern recognition Utilization of clouds, Sensors, Actuators, MPC Early detection and control of process fluctuation Crosslinking of process and economic causes Reduction of operator specific KPI`s Elevated attention to ensure 24/7 reliability of sensors, actuators and software by residential and remote access

14 Process fluctuation Who is a client for next level digitization? Runs a complex industrial manufacturing process Is unsatisfied with cost AVAILABILITY Suffers unexpected process fluctuations RELIABILITY

15 Papermaking Introduction The sum of three big talents in a "system of systems" RELIABILITY Visualize, Stabilize & Optimize (The modular solution: Sensors, controls, actuators) AVAILABILITY Predictive Maintenance (Intelligent, condition based: CMS, CMMS, diagnostics) Pm 4.0 The Service you need before you know! (Analytics, remote, upgrades). 15

16 The digital portfolio to stabilize complex industrial issues is modular. More elements to come. RELIABILITY AVAILABILITY IoT OnEfficiency Cockpit OnEfficiency Dewatering OnEfficiency Strengths OnEfficiency Curl* OnCare Mex OnCare CM OnCare AM Compilation & Integration From the sensor to the cloud infra structure services emerging technologies OnEfficiency DIP * Demo 1st Qu 2017

17 OnE Cockpit: Easy-to-grasp Visualization

18 Cockpit function. Every information must be relevant to the issue and meaningful for a fast decision-making. Actual measured value Actual measured value with critical limits Min/Max of the last 4hrs Status flag 4 hr forecast Instant trend access Instant PCS access

19 Result Result Result Actuators in sheet forming The sheet forming process A fast changing cycle driven by 8 interdependent actuators. Cycle starts by flocculation followed by shear in headbox. Polymer type Polymer amount Retention Polymer type Polymer amount Fiber/Ash type + amount Fiber/Ash type + amount Dilution: Lip slice opening Dilution: Lip slice opening Speed: V PM /Jet:Wire Vacua < 200 msec WWater Speed: V PM /Jet:Wire Pulsation: Blade action WWater charge load Dewatering Flocculation Dry content pickup SHEAR Formation Press performance Energy consumption Fabrics wear Basis weigth ash content Stiffness Strengths Porosity

20 Time scale in a sheet forming process Example GAP-Former 1500 m/min The diffusor destroys any floc created before head box. The sheet is created by REFLOCCULATION. Flocculation zone Immobile sheet Time after Diffusor: 0.16 s Wire speed: 1500 m/min (25 m/s) Distance to Immobility 4 m Time to Diffusor: 9.6 s Pipe diameter: DN 800 Flow to Headbox: 110,000 l/min Flow Speed: 3,64 m/s Distance to Diffusor 35 m Time to Diffusor: 6.9 s Pipe diameter: DN 800 Flow to Headbox: 110,000 l/min Flow Speed: 3,64 m/s Distance to Diffusor 25 m Time to Diffusor: 4.5 s Pipe diameter: DN 800 Flow to Headbox: 100,000 l/min Flow Speed: 3,32 m/s Distance to Diffusor 15 m Insufficient (~ 10%) retention without reflocculation Total flocculation time max 9.6 sec Reflocculation time max 0.16 sec

21 Novel algorithms have been developed to control actuators stabilizing the entire sheet creation process Formation / Porosity Formation Formation Formation Lip slice opening Porosity Porosity Bottom wire tension Forming Roll-Vacua Porosity Lip slice opening Bottom wire tension Forming Roll-Vacua Operating area

22 Field results: OnEfficiency Dry Line Control Double ply board, tpy Dewatering Control Dry Content (FormingSens) Manual operation Automatic control OCC Ratio Slice Lip Wire Speed Basis Weight Refiner Load Former Vacuum Dry line stable despite changes in -refining -dewatering -lip sclie opening Less energy costs More constant quality paper production

23 OnEfficiency Strength Realtime Control of strength in packaging

24 OnEfficiency Strength Lay out for doube ply board tons p.a. Start up: Aug/Sept Start up: Feb OnE Cost Manager Dry line control Strength Control Furnish ratio control Refiner control Virtual STFI Mullen OnEfficiency - Mondi Group J. Flitsch J/W BW Vac

25 The virtual Sensor predicts strength data realtime STFI and Mullen High confidence interval: ± 2.5%; Field test double ply tons p.yr Virtual Sensor Lab STFI Virtual Sensor Lab Mullen

26 Field results B & P: OnE Strength Double ply board, tons per yr, February 2016 Manual control Dry weight Jet/wire ratio STFI 1.5# OnEfficiency strength active Min spec Results Basis weight set point reduced from 55# to 53.5# (-20 tons/d fiber) Fiber savings 20 tons/d J/W ratio from 30ft to 40ft STFI stable on preselected setpoints

27 Process fluctuations Tomorrow: A pivotal new level of transparency & controls. Stabilizing processes to meet target KPIs. Raw materials Fluctuation Corridor Equipment visualize stabilize optimize Stabilized Corridor People New Target Corridor Waste of resources Time Variance of input factors Different behavior of individual PMs High variance of outputs, instable processes Rationally automated stabilization

28 OnCare a part of the jigsaw Papermaking 4.0 CUSTOMER CUSTOMER PM 4.0 Services SAP MES- System ERP- System TES OnCall OnVideo SONAR Self learning and self adjusting control processes enable an optimized operation OnCare AM Cyber Physical Systems A continous exchange condition data enable individual maintenance strategies for each object through out the entire life cycle OnCare CM OnE OnC OnQ Papermaking 4.0

29 OnCare AM mobile solution Wi-Fi Object code: PM02. Broke-Pulper 1. Agitator 2. Motor Local or Cloud

30 OnCare - Augmented Reality in Preventive Maintenance Navigation Mode Inspection Mode Inspection Route Identifying and showing hidden objects Object status at a glance to prevent redundant work order requests Arrow is showing route direction Inspection route including task list and work order request generation Equipment view with documents, maintenance history and engineering data Prepared for Voith Cloud database support in Papermaking 4.0

31 Benefits - OnCare All maintenance data already included Predefined maintenance processes Integrated condition monitoring system Applicable for mobile solutions (e.g. tablet pc) Combines manufacturer and maintenance know-how Very short implementation time

32 OnCare Maintenance Excellence Optimization Program Case study in North America Comparison of Technical Data Before Target after 24 months Machine uptime [%] 92 >95 Machine production [tpd] 820 >1,000 Machine speed at reel [fpm] Maintenance cost [$/ton] 37 <27 Maintenance cost optimization Actions to reach the Target Maintenance Excellence with OnCare cost optimum Maintenance Excellence Content Implement best practices for shutdown planning & scheduling (MEx) Implement best practices for planning & scheduling, non-shutdown (MEx) Development of a risk based reliability maintenance program (MEx)

33 Why Voith? Big Steel meets Big Data Top Papermaking Know-how Over 150 years experience in paper industry Over 300 Process and Plant experts A local yet global partner Top Digital Expertise Users / 14 Global Data Centres Over 600 Automation, IT specialists and 34 computer security experts Cross Industry Platforms

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