Case Study: Quality Study 2.pdf · Case Study: Quality Mineral beneficiation Introduction Case...

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Copyright © 2013, Industrial Management Enhancement email: [email protected] // www.imeSolutions.biz Page 1 of 4 Case Study: Quality Mineral beneficiation Introduction Case Study 2 originates from a mineral processing plant. Primary crushing and milling precedes the flotation circuit. All processing prior to the flotation circuit is about getting material in the correct format to maximise recovery of minerals. Incorrect flotation circuit operation results in significant losses. This assessment quantifies the impact of Rougher Mass Pull in relation to flotation circuit performance. Control samples, sampled every two hours, provide feedback regarding quality. A combination of process data (flow rates, motor current, pH, feed rates, etc.) and control samples describe process conditions. The aim is to understand how process conditions relate to flotation performance that is reported retrospectively (i.e. control samples lagging the realtime process by a minimum of 2 hours). This assessment provides insight into operating conditions that have the highest probability of realising the desired performance (expressed in terms of recovery, grade and production rate). Once agreement is reached on the baseline state, it will be possible to generate a TISM to describe Rougher Mass Pull in realtime. The latter serves as an early warning system when the process is drifting away from the baseline state thereby facilitating proactive management of the process. Information produced during this assessment facilitates root cause analysis, tracks the impact of performance improvement initiatives, and facilitate training / development of operational personnel. Opportunity Description Rougher Mass Pull has a direct impact on recovery. In this particular case, 1% loss in recovery per day is equivalent to about USD12000 revenue loss – that is mineral not recovered and pumped to tailings. Key Process Influencing Factors identified for this flotation circuit include Mill Feed Rate, Pulp Density, Reagent Dosing, Circulating Load, Rougher Concentrate Tank Level, Froth Depth, and Volumetric Air Flow on Mechanism. Although a control system (PLC) controls process variables against set points, operational decisionmaking rated as the most significant factor contributing toward Rougher Mass Pull Control. Guidelines were put in place regarding appropriate manner the rougher circuit should be operated. Irrespective of the latter, mass pull regularly operated outside the target range resulting in spillage and recovery losses as the residence time in the Cleaner / Recleaner circuit goes outside defined limits.

Transcript of Case Study: Quality Study 2.pdf · Case Study: Quality Mineral beneficiation Introduction Case...

Page 1: Case Study: Quality Study 2.pdf · Case Study: Quality Mineral beneficiation Introduction Case Study 2 originates from a mineral processing plant. Primary crushing and milling precedes

     

Copyright © 2013, Industrial Management Enhancement 

e‐mail: [email protected] // www.imeSolutions.biz    Page 1 of 4  

CaseStudy:QualityMineralbeneficiation

Introduction 

Case Study 2 originates from a mineral processing plant. Primary crushing and milling precedes the 

flotation circuit. All processing prior to the flotation circuit is about getting material in the correct 

format to maximise recovery of minerals. Incorrect flotation circuit operation results in significant 

losses. 

This  assessment  quantifies  the  impact  of  Rougher  Mass  Pull  in  relation  to  flotation  circuit 

performance.  

Control  samples,  sampled every  two hours, provide  feedback  regarding quality. A  combination of 

process  data  (flow  rates,  motor  current,  pH,  feed  rates,  etc.)  and  control  samples  describe 

process conditions.  

The aim  is  to understand how process conditions  relate  to  flotation performance  that  is  reported 

retrospectively (i.e. control samples lagging the real‐time process by a minimum of 2 hours). This 

assessment  provides  insight  into  operating  conditions  that  have  the  highest  probability  of 

realising the desired performance (expressed in terms of recovery, grade and production rate). 

Once agreement is reached on the baseline state, it will be possible to generate a TISM to describe 

Rougher Mass Pull in real‐time. The latter serves as an early warning system when the process is 

drifting away from the baseline state thereby facilitating pro‐active management of the process. 

Information  produced  during  this  assessment  facilitates  root  cause  analysis,  tracks  the  impact  of 

performance  improvement  initiatives,  and  facilitate  training  /  development  of  operational 

personnel. 

Opportunity Description 

Rougher Mass Pull has a direct  impact on recovery.  In this particular case, 1%  loss  in recovery per 

day is equivalent to about USD12000 revenue loss – that is mineral not recovered and pumped to 

tailings.  

Key  Process  Influencing  Factors  identified  for  this  flotation  circuit  include Mill  Feed  Rate,  Pulp 

Density,  Reagent Dosing,  Circulating  Load,  Rougher  Concentrate  Tank  Level,  Froth Depth,  and 

Volumetric Air Flow on Mechanism. Although a control system  (PLC) controls process variables 

against set points, operational decision‐making rated as the most significant factor contributing 

toward Rougher Mass Pull Control. 

Guidelines were put in place regarding appropriate manner the rougher circuit should be operated. 

Irrespective  of  the  latter, mass  pull  regularly  operated  outside  the  target  range  resulting  in 

spillage and recovery losses as the residence time in the Cleaner / Re‐cleaner circuit goes outside 

defined limits.  

Page 2: Case Study: Quality Study 2.pdf · Case Study: Quality Mineral beneficiation Introduction Case Study 2 originates from a mineral processing plant. Primary crushing and milling precedes

     

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The need existed,  firstly,  to determine whether existing process parameters  could provide  insight 

into  operating  conditions  delivering  best  performance.  Secondly,  utilize  Performance Maps  to 

determine how long the Rougher Mass Pull operated within desired limits – this is to quantify the 

operational  risk exposure. Thirdly, utilize Performance Maps  to align all  stakeholders  regarding 

the  correct  operating  procedure.  In  other words,  standardize  the  Rougher  Circuit method  of 

operation. 

Approach 

Figure  1  is  an  extract  of  the  Performance Maps  constructed  to  characterize  process  conditions 

associated with Rougher Mass Pull. 

 

Figure 2 maps the relationship between process conditions and Recovery. The bold and underlined 

conditions  represent highest  recovery.  (The  selection  took other constraints  such  tailing grade, 

feed grade, motor currents, levels, etc. into account. In other words, if any of the qualifying Key 

Process Influencing Factors were outside their respective ranges, it disqualifies the position to be 

included as an ‘ideal’ condition.) 

Figure 1 - Performance Map for Rougher Mass Pull 

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Figure 4 contains the matching conditions selected in Figure 2. Figure 4 contains a clear definition of 

what  operating  conditions  constitutes  ideal  operation.  In  other  words,  the  probability  of 

achieving higher recovery substantially improves when operating within the selected condition.  

The  ability  to  link  a  performance  indicator  to  operating  conditions  using  process measurements 

confirms that it is possible to utilize process parameters to detect operating conditions (this was 

the first objective of the study).   

 

 

 

Figure 3 confirms that the Rougher operated for only 9.2% within the target state. This Performance 

Map  took 20 days of operation  into account. During  ideal conditions, recovery was 71% versus 

non‐ideal  conditions  that  reported 64%  (weighted average). This  is equivalent  to a 7% drop  in 

recovery  over  18.2  days.  In  monetary  terms,  this  is  equivalent  to  USD1.5m  loss  (second 

objective). 

Figure 2 - Recovery 

Figure 3 - Time-in-State 

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KPIF Decision Rationale 

Stakeholders participated  in  this assessment. Performance Maps  linked process measurements  to 

recovery.  During  interactive  discussions,  operational  personnel  gained  insight  into  the 

contribution of various Key Process  Influencing Factors. This understanding provided a common 

approach to Rougher Mass Pull control (objective number three). 

Conditions outlined by Performance Maps provide a quantitative assessment of process conditions 

facilitating efficient decision‐making. 

 

Summary of Results and Benefits 

A  follow‐up  study  conducted  three weeks  after  aligning  stakeholders  revealed  that  the  average 

Time‐in‐State (ideal state) increased from 9.2% to 65%. Recovery increased at the same time by 

an average of 2.1% after discounting feed grade changes. 

Figure 4 – Rougher Mass Pull – ‘Ideal’ conditions