IMPROVING THE ACCURACY OF WEIGHT MEASUREMENT IN PROCESS CONTROL FOR CONTINUOUS STEEL CASTING

MGT 5311 GROUP 5

IntroductionCommercial Metals Company

Commercial Metals Company (CMC)- Global leader in steel recycling and manufacturing

- Operations include low-cost metals recycling, manufacturing, fabrication and trading enterprises with over 200 locations in more than 20 countries

IntroductionCMC Steel Texas

Commercial Metals Company (CMC)- The mill in Seguin, TX is the first of 5 US mills operated by CMC and has been in service since 1947.

- Products & Services include raw steel billets, angle/channel, rebar, and other long bar products

Continuous Steel CastingProcess overview

Continuous Steel CastingProcess overview

BILLET

DEFINE

Define the problem :

Billets coming from the caster vary greatly from the target weight established to maximize rolling yield, creating waste in every billet

Project scoping :

To reduce the variability of billet weight (CTQ) and to improve the accuracy of measures taken in the casting process for maximizing yield efficiency

Targeted equipment:

Caster withdraw rollers, cutting torches, and billet weighing system

Problem Statement

DEFINESteel casting process flowchart

MEASURECaster process control - Swimlane diagram

MEASURE

● Distributed control systems (DCS)

Level 2 caster data

ANALYZE

Raw billet weight data - weight variation over time

ANALYZE

Raw billet weight data - regression fit of length/width ratio

ANALYZE

Raw billet weight data - frequency of “+64” billets

ANALYZE

Online v. offline scale comparison - control charts

ANALYZE

Online v. offline scale comparison - measured weight vs. target

ANALYZE

Online v. offline scale comparison - Cpk charts

ANALYZE

Root cause analysis - fishbone diagram

IMPROVE

● The problems are specific and technical in nature therefore incremental corrective actions and improvements by the process owners (shop floor, QA, Caster Maintenance) should be the main focus

● Improvement Goals:o Improve the accuracy of measures used in process controlo Make improvements to systems contributing to variation in billet weight

to improve yield in the rolling mill

Overview of process improvement goals

IMPROVE

● Process Mapping Improvement - Revised Swimlane

● Poka-Yoke or Mistake Proofing

● Empower Process Owners

Suggestions for Improvements

IMPROVEProcess Control Improvements - Revised Swimlane

IMPROVEPoka-Yoke: Mistake Proofing by Automating

New Standards and Procedures on Calibration● Online billet scale:

o Calibration frequencyo Oscillation filtering

● Billet length verification

Automate Control Adjustments using SPC data in Level 2

● New billet weight targets and control limits must be determined ● Monitor process control charts automatically and reliably● Make automatic adjustments to the torch cutters in response to out-of-

control trends

IMPROVE

Process Owners (Caster floor operators, QA) need to:

● Understand: The general process and the desired outcomes

Steps of process assigned to themHow their actions affect the operations in other sections of the process

● Appreciate:The significance of collaboration

● Know:Their input matters and is respectedThey are enabled to make spot on decisions for timely corrective actions

● Acquire:Six Sigma Green Belt training on methods and certification. Provide incentives through education reimbursements

Empower the Worker: Knowledge Management & Engagement

CONTROL

Ultimately, we need to track, monitor and maintain performance of key measures by ensuring key variables remain within the maximum acceptable ranges under the modified process. Therefore, we want to

ensure that measurements continue to be reliable, accurate,and verifiable

CONTROLContinuous improvement - Deming Cycle

CONTROL

Maintain new standards and procedureso Proper documentation: SOPs, Dashboard and

scorecards, inspection reports, test data, audit reports, calibration

o Internal auditso Periodic status reviews by process owners to

self-check their performance

“CHECK”

CONTROL

Maintain Control Limitso Regular use of statistical process control charts with

data gathered and interpreted automatically

o Reach optimal range of standard deviation, mean, UCL and LCL

“ACT”

CONCLUSION

● Data collection and measurement error prevents reliable use of SPC for weight measurement/mill yield control

● Cleanup of data highlights weaknesses in procedure, measurement, data recording, and knowledge management in addition to steel casting defects

● To reduce and control defects, a foundation for continuous PDCA improvements must be put in place:

Suggestions for immediate improvement: Revise process map to communicate procedure, automate control systems using reliable SPC data, integrate knowledge management, and plan for new standards and procedures

● Future improvements: Use foundation of reliable measurement and interpretation to improve yield via PDCA cycle