This document describes a Six Sigma project to improve the batch record system for packaging two products: Ponstan 500 mg Film Coated Tablet (FCT) and Terramycin (TM) Oph. Ointment. The project goal is to reduce the packaging lead time for both products. Data was collected on packaging and total manufacturing lead times. Analysis found that the batch record review process contributes significantly to delays, with production review time being the largest portion. Brainstorming identified potential causes for long review times including inefficient review processes and lack of standard lead times. Charts show variability in the number of batch records sent to QA daily and waiting times for lab test results needed for QA review.
The document discusses measuring manufacturing cycle efficiency through calculating manufacturing cycle efficiency (MCE). MCE is defined as the value added time divided by the total cycle time. It provides two examples to demonstrate how MCE can be calculated and used to track process improvements over time. The document also discusses using takt time as a meaningful measurement gauge to ensure customer demand is met. Takt time is defined as the total available time divided by customer demand. Using takt time, the expected cycle time for each process can be calculated to meet production goals.
This document summarizes a project to reduce waste from a Klikklok machine that packages pies at a food manufacturing plant. The machine was contributing to production targets not being met. The Six Sigma DMAIC methodology was used. Data showed the machine wasted 14.11% of time. Root causes were identified using a cause-and-effect diagram. Loader arms on the machine were replaced, significantly reducing waste. Ongoing monitoring using control charts and a preventative maintenance calendar was recommended to sustain the improvements.
Quality management aims to continuously improve processes to meet customer needs and reduce defects. It encompasses tools like statistical process control (SPC), which uses control charts to monitor processes for abnormal variation. Control charts have upper and lower control limits to detect assignable causes of variation. P-charts are used for attributes where outcomes are pass/fail, while X-bar and R-charts are used for variables with sample means and ranges. Capability indices like Cpk indicate if a process can produce within specifications. Continuous improvement requires preventing defects through tools like fishbone diagrams, histograms, and Pareto charts to prioritize issues.
Six sigma-in-measurement-systems-evaluating-the-hidden-factoryManuel Peralta
The document summarizes a case study evaluating the measurement system used to measure a critical quality trait (CTQ1) of an internal raw material (A1) produced at four worldwide locations. A measurement study analysis found the measurement system had a high %GRR (>90%) and poor discrimination, indicating significant measurement error. Results varied by location, with one site showing a statistically significant difference in CTQ1 mean compared to others. Improving the measurement system could help reduce hidden factory waste from over-processing and lead to cost savings.
The document discusses a case study evaluating the measurement system for a key quality variable (CTQ1) at W.R. Grace. A measurement systems analysis was conducted across four sites measuring CTQ1. The results showed high measurement variation compared to process variation, with an overall %GRR of 94.3. While some sites had acceptable P/T ratios and variation, the overall system lacked discrimination. Improving the measurement system accuracy and precision could help reduce hidden factory costs and further process improvements.
Quality andc apability hand out 091123200010 Phpapp01jasonhian
The document outlines key concepts in quality management and Six Sigma methodology. It discusses definitions of quality, total quality management (TQM), and Six Sigma. Six Sigma aims to reduce defects through eliminating variation and achieving near zero defect levels. It uses a Define-Measure-Analyze-Improve-Control (DMAIC) methodology. Statistical process control charts and process capability indices are also introduced to measure quality performance. An example of Mumbai's successful lunch delivery system achieving over 5-sigma quality levels is provided.
The document discusses measuring manufacturing cycle efficiency through calculating manufacturing cycle efficiency (MCE). MCE is defined as the value added time divided by the total cycle time. It provides two examples to demonstrate how MCE can be calculated and used to track process improvements over time. The document also discusses using takt time as a meaningful measurement gauge to ensure customer demand is met. Takt time is defined as the total available time divided by customer demand. Using takt time, the expected cycle time for each process can be calculated to meet production goals.
This document summarizes a project to reduce waste from a Klikklok machine that packages pies at a food manufacturing plant. The machine was contributing to production targets not being met. The Six Sigma DMAIC methodology was used. Data showed the machine wasted 14.11% of time. Root causes were identified using a cause-and-effect diagram. Loader arms on the machine were replaced, significantly reducing waste. Ongoing monitoring using control charts and a preventative maintenance calendar was recommended to sustain the improvements.
Quality management aims to continuously improve processes to meet customer needs and reduce defects. It encompasses tools like statistical process control (SPC), which uses control charts to monitor processes for abnormal variation. Control charts have upper and lower control limits to detect assignable causes of variation. P-charts are used for attributes where outcomes are pass/fail, while X-bar and R-charts are used for variables with sample means and ranges. Capability indices like Cpk indicate if a process can produce within specifications. Continuous improvement requires preventing defects through tools like fishbone diagrams, histograms, and Pareto charts to prioritize issues.
Six sigma-in-measurement-systems-evaluating-the-hidden-factoryManuel Peralta
The document summarizes a case study evaluating the measurement system used to measure a critical quality trait (CTQ1) of an internal raw material (A1) produced at four worldwide locations. A measurement study analysis found the measurement system had a high %GRR (>90%) and poor discrimination, indicating significant measurement error. Results varied by location, with one site showing a statistically significant difference in CTQ1 mean compared to others. Improving the measurement system could help reduce hidden factory waste from over-processing and lead to cost savings.
The document discusses a case study evaluating the measurement system for a key quality variable (CTQ1) at W.R. Grace. A measurement systems analysis was conducted across four sites measuring CTQ1. The results showed high measurement variation compared to process variation, with an overall %GRR of 94.3. While some sites had acceptable P/T ratios and variation, the overall system lacked discrimination. Improving the measurement system accuracy and precision could help reduce hidden factory costs and further process improvements.
Quality andc apability hand out 091123200010 Phpapp01jasonhian
The document outlines key concepts in quality management and Six Sigma methodology. It discusses definitions of quality, total quality management (TQM), and Six Sigma. Six Sigma aims to reduce defects through eliminating variation and achieving near zero defect levels. It uses a Define-Measure-Analyze-Improve-Control (DMAIC) methodology. Statistical process control charts and process capability indices are also introduced to measure quality performance. An example of Mumbai's successful lunch delivery system achieving over 5-sigma quality levels is provided.
The document summarizes a value stream mapping project for a pilot plant producing a new product. The pilot plant runs trials of compounds developed in R&D to test commercial production feasibility. It aims to deliver 50kg of the product per month to customers in 3kg batches on a weekly schedule. The value stream mapping shows that raw materials currently sit in the warehouse for 10 days before processing, and intermediate and finished products also accumulate inventory before pulling by customers. Areas for improvement include reducing inventory times, increasing uptime of key processes like reaction and distillation, and decreasing changeover times across processes.
This document provides a summary of a lean assessment conducted at Acme Machell in March 2011. The objective was to reduce past due parts from 69,694 to zero by April 2011 and provide an assessment to create an action plan for process improvements. It identified key problems, such as excessive lead times and work-in-progress. It analyzed two value stream maps and proposed improvements like setup reduction, visual management, and combining operations. Recommended actions included SMED, TPM, reducing scrap, and work instruction standardization. Overall scores of 1.55 indicated opportunities in standardizing operations, visual controls, and 5S practices. The next step is for Acme to develop an action plan to eliminate backlogs and sustain improvements
The document discusses a case study measuring a critical quality trait (CTQ1) at a manufacturing company. A measurement study of CTQ1 was conducted across four worldwide sites to evaluate the measurement system. The results showed high measurement error, with an overall %GRR of 94.3% and P/T ratio of 116%. When analyzed by site, two sites showed significant differences in CTQ1 averages. The high measurement variability masked potential process improvements. Improving the measurement system capability could help the company better understand real process variation and identify opportunities to optimize production.
The document summarizes the efforts of a team to improve the rigid laminate scheduling system at a manufacturing plant. Key changes included decoupling scheduling from sales orders, scheduling the press based on the top 5 master sheet parts to better manage variation, and batching odd rigid orders to be processed twice per month. These changes reduced unnecessary changeovers, late shipments, and inventory levels. Metrics showed improvements like a 14% increase in plant capacity and a 13% reduction in master sheet work-in-process inventory.
The document discusses metrics for tracking a project's test management process. It provides examples of metrics that could be captured at different stages of the testing lifecycle, including test execution rates, defect rates, requirements tracing, and environment issues. Guidelines are also presented for establishing a process to define, collect, analyze, and report on metrics on a regular basis to improve visibility and decision making.
This document discusses topics related to quality control and total quality management (TQM). It includes a list of presenters and topics. Some key topics summarized are:
- The difference between quality assurance (management plan to guarantee integrity of data) and quality control (series of analytical measurements to assess quality).
- The 7 basic tools of quality control including process flow charts, control charts, and Pareto analysis.
- An introduction to TQM principles in India where companies started adopting techniques like statistical process control, quality circles, and ISO standards.
- Statistical quality control methods like acceptance sampling and process sampling.
- Calculations of mean, standard deviation, capability index, and probability of defects.
This document discusses the importance of quality management (QM) in the mining sector. QM involves proactively monitoring quality control data over time to detect trends or biases and ensure consistent results. The document provides examples of how QM can be applied across various stages, including sample collection, preparation, and chemical analysis. It emphasizes that averages alone may mask issues and QM allows for real-time assessment to close gaps. QM helps ensure sustainable and stable business decisions by maintaining consistent quality throughout the sampling and analysis process.
The document discusses a case study involving the evaluation of a measurement system for an important quality variable, CTQ1, at W.R. Grace. A measurement systems analysis (MSA) study was conducted involving the four worldwide sites that produce the raw material. The results showed a high %GR&R of 94.3% and P/T ratio of 116%, indicating significant measurement error. When analyzed separately, the sites showed varying levels of measurement capability, with one site having a %GR&R of 38.9%. The MSA study identified opportunities to improve the measurement system and link it back to process improvements.
CASE STUDY ON IMPLEMENTATION OF KAIZEN AND 5S TECHNIQUES IN SMALL MANUFACTURI...Shubhangi Gurway
The document presents a presentation on implementing Kaizen and 5S techniques in a PVC pipe manufacturing company. It discusses introducing Kaizen and 5S concepts, aims to improve productivity and reduce stock outs. It outlines the methodology used including selecting a company facing issues like long lead times and stock outs. An analysis found the current stock out probability is 50% with the safety stock of 18 units not being scientifically determined. Areas for improvement were identified like raw material storage. Countermeasures included preparing Kaizen sheets, 5S sheets, and computerizing inventory data maintenance to scientifically calculate the required safety stock level.
Enforcement from the Inside: Improving Quality of Business in Process ManagementTobias Unger
The document proposes a concept for modeling exceptional situations and triggering corrective actions in business processes. Constraints are defined and attached to activities or scopes in a process. Metrics provide input data for constraint parameters, which are evaluated at defined points to detect violations. If violated, a constraint handler executes additional logic, either concurrently or by terminating the normal flow. The concept was implemented by mapping constraint handlers to existing BPEL constructs like fault and event handlers to integrate it with BPEL engines without extending the language. Future work includes implementing the capabilities in a BPEL engine and exploring dynamic constraint binding.
The document discusses Lean methodology which focuses on eliminating waste to produce high quality products faster and at lower cost. Lean aims to streamline processes through techniques like single piece flow, just-in-time production, and eliminating non-value added activities to improve throughput, quality, and customer satisfaction. Key aspects of Lean covered include value stream mapping, reducing the seven wastes, line balancing, managing bottlenecks, setup reduction, pull systems, and visual management.
The document summarizes an improvement project to increase productivity in bulk operations at a noodle manufacturing plant. It provides data showing current productivity levels are 14 kg/man hour on average across manual and machine bulk filling. A project charter was developed with the goal of increasing productivity by 30% through analyzing processes, collecting data on output and stoppages, and identifying causes of low productivity such as the bulk machine running slow and lack of training. The document outlines the project team, timeline, and plan to measure improvements through increased daily production and optimized manpower utilization.
Six sigma-in-measurement-systems-evaluating-the-hidden-factory (2)Bibhuti Prasad Nanda
The document discusses a case study conducted at W.R. Grace to evaluate the measurement system for an important quality variable, CTQ1, at four worldwide production locations. An MSA study was performed to determine the %GRR, P/T ratio, and bias of the CTQ1 measurement. The results showed high measurement variation contributed by the operators and interactions between operators and samples. Process data was then linked to the MSA study, showing representative samples were selected and improvements to the measurement system could reduce hidden factory costs from over-processing and rework.
A case study on productivity improvement of wearing insert and cutting ringIJECSJournal
The objective of this paper is to present case study on a wearing insert and cutting ring for the efficient improvements in productivity with the help of various work Study Methods. In this study productivity is improved through identifying the process that involves the time required for the process as the main reason to achieve the objectives of increasing the productivity. Time and motion study is one of the necessary factors to set a standard target. The study is aimed at identifying the unwanted work processes which in turn increases the time required, efforts as well as the cost of the product. Thus the changes were made in the areas which require improving using work study methods.
Overview of 3 day Lean & Kaizen Course ContentTimothy Wooi
This document outlines the content of a 3-day Lean & Kaizen course. Day 1 covers topics like Lean Manufacturing principles, characteristics of Lean production including cellular layouts and Kanban systems. Day 2 focuses on standard work including takt time and pull production. Day 3 covers tools for standard work, Total Productive Maintenance (TPM), and Kaizen workshops which use small group projects to drive continuous improvement. The workshop method involves planning, implementing improvements on the production floor for a week, and follow up meetings to sustain results.
This project aimed to reduce paste usage and costs on Backing Line 4 by improving the calendar roll, backing roll, and installing new measurement tools. Goals included installing a new nip station, controlling paste temperature to manage viscosity, and using a Terahertz thickness gauge to eliminate destructive testing. The project achieved a cost savings of $1.7 million annually within one month by installing temporary new rolls. Controlling paste temperature and installing the gauge were ongoing. Success criteria included reducing paste usage and providing real-time thickness measurements for better process control.
The document provides information about fabrics finishing processes at Famkam Dyeing Ltd. It includes:
1. An introduction to fabrics finishing and its objectives.
2. Flow charts showing the finishing process and organizational structure.
3. Details of finishing machines including specifications.
4. Standard operating procedures and quality management systems.
5. Job responsibilities of finishing department staff.
6. Parameters for processes like heat setting and guidelines for chemical use.
Cover Story - China's Investment Leader - Dr. Alyce SUmsthrill
In World Expo 2010 Shanghai – the most visited Expo in the World History
https://www.britannica.com/event/Expo-Shanghai-2010
China’s official organizer of the Expo, CCPIT (China Council for the Promotion of International Trade https://en.ccpit.org/) has chosen Dr. Alyce Su as the Cover Person with Cover Story, in the Expo’s official magazine distributed throughout the Expo, showcasing China’s New Generation of Leaders to the World.
The document summarizes a value stream mapping project for a pilot plant producing a new product. The pilot plant runs trials of compounds developed in R&D to test commercial production feasibility. It aims to deliver 50kg of the product per month to customers in 3kg batches on a weekly schedule. The value stream mapping shows that raw materials currently sit in the warehouse for 10 days before processing, and intermediate and finished products also accumulate inventory before pulling by customers. Areas for improvement include reducing inventory times, increasing uptime of key processes like reaction and distillation, and decreasing changeover times across processes.
This document provides a summary of a lean assessment conducted at Acme Machell in March 2011. The objective was to reduce past due parts from 69,694 to zero by April 2011 and provide an assessment to create an action plan for process improvements. It identified key problems, such as excessive lead times and work-in-progress. It analyzed two value stream maps and proposed improvements like setup reduction, visual management, and combining operations. Recommended actions included SMED, TPM, reducing scrap, and work instruction standardization. Overall scores of 1.55 indicated opportunities in standardizing operations, visual controls, and 5S practices. The next step is for Acme to develop an action plan to eliminate backlogs and sustain improvements
The document discusses a case study measuring a critical quality trait (CTQ1) at a manufacturing company. A measurement study of CTQ1 was conducted across four worldwide sites to evaluate the measurement system. The results showed high measurement error, with an overall %GRR of 94.3% and P/T ratio of 116%. When analyzed by site, two sites showed significant differences in CTQ1 averages. The high measurement variability masked potential process improvements. Improving the measurement system capability could help the company better understand real process variation and identify opportunities to optimize production.
The document summarizes the efforts of a team to improve the rigid laminate scheduling system at a manufacturing plant. Key changes included decoupling scheduling from sales orders, scheduling the press based on the top 5 master sheet parts to better manage variation, and batching odd rigid orders to be processed twice per month. These changes reduced unnecessary changeovers, late shipments, and inventory levels. Metrics showed improvements like a 14% increase in plant capacity and a 13% reduction in master sheet work-in-process inventory.
The document discusses metrics for tracking a project's test management process. It provides examples of metrics that could be captured at different stages of the testing lifecycle, including test execution rates, defect rates, requirements tracing, and environment issues. Guidelines are also presented for establishing a process to define, collect, analyze, and report on metrics on a regular basis to improve visibility and decision making.
This document discusses topics related to quality control and total quality management (TQM). It includes a list of presenters and topics. Some key topics summarized are:
- The difference between quality assurance (management plan to guarantee integrity of data) and quality control (series of analytical measurements to assess quality).
- The 7 basic tools of quality control including process flow charts, control charts, and Pareto analysis.
- An introduction to TQM principles in India where companies started adopting techniques like statistical process control, quality circles, and ISO standards.
- Statistical quality control methods like acceptance sampling and process sampling.
- Calculations of mean, standard deviation, capability index, and probability of defects.
This document discusses the importance of quality management (QM) in the mining sector. QM involves proactively monitoring quality control data over time to detect trends or biases and ensure consistent results. The document provides examples of how QM can be applied across various stages, including sample collection, preparation, and chemical analysis. It emphasizes that averages alone may mask issues and QM allows for real-time assessment to close gaps. QM helps ensure sustainable and stable business decisions by maintaining consistent quality throughout the sampling and analysis process.
The document discusses a case study involving the evaluation of a measurement system for an important quality variable, CTQ1, at W.R. Grace. A measurement systems analysis (MSA) study was conducted involving the four worldwide sites that produce the raw material. The results showed a high %GR&R of 94.3% and P/T ratio of 116%, indicating significant measurement error. When analyzed separately, the sites showed varying levels of measurement capability, with one site having a %GR&R of 38.9%. The MSA study identified opportunities to improve the measurement system and link it back to process improvements.
CASE STUDY ON IMPLEMENTATION OF KAIZEN AND 5S TECHNIQUES IN SMALL MANUFACTURI...Shubhangi Gurway
The document presents a presentation on implementing Kaizen and 5S techniques in a PVC pipe manufacturing company. It discusses introducing Kaizen and 5S concepts, aims to improve productivity and reduce stock outs. It outlines the methodology used including selecting a company facing issues like long lead times and stock outs. An analysis found the current stock out probability is 50% with the safety stock of 18 units not being scientifically determined. Areas for improvement were identified like raw material storage. Countermeasures included preparing Kaizen sheets, 5S sheets, and computerizing inventory data maintenance to scientifically calculate the required safety stock level.
Enforcement from the Inside: Improving Quality of Business in Process ManagementTobias Unger
The document proposes a concept for modeling exceptional situations and triggering corrective actions in business processes. Constraints are defined and attached to activities or scopes in a process. Metrics provide input data for constraint parameters, which are evaluated at defined points to detect violations. If violated, a constraint handler executes additional logic, either concurrently or by terminating the normal flow. The concept was implemented by mapping constraint handlers to existing BPEL constructs like fault and event handlers to integrate it with BPEL engines without extending the language. Future work includes implementing the capabilities in a BPEL engine and exploring dynamic constraint binding.
The document discusses Lean methodology which focuses on eliminating waste to produce high quality products faster and at lower cost. Lean aims to streamline processes through techniques like single piece flow, just-in-time production, and eliminating non-value added activities to improve throughput, quality, and customer satisfaction. Key aspects of Lean covered include value stream mapping, reducing the seven wastes, line balancing, managing bottlenecks, setup reduction, pull systems, and visual management.
The document summarizes an improvement project to increase productivity in bulk operations at a noodle manufacturing plant. It provides data showing current productivity levels are 14 kg/man hour on average across manual and machine bulk filling. A project charter was developed with the goal of increasing productivity by 30% through analyzing processes, collecting data on output and stoppages, and identifying causes of low productivity such as the bulk machine running slow and lack of training. The document outlines the project team, timeline, and plan to measure improvements through increased daily production and optimized manpower utilization.
Six sigma-in-measurement-systems-evaluating-the-hidden-factory (2)Bibhuti Prasad Nanda
The document discusses a case study conducted at W.R. Grace to evaluate the measurement system for an important quality variable, CTQ1, at four worldwide production locations. An MSA study was performed to determine the %GRR, P/T ratio, and bias of the CTQ1 measurement. The results showed high measurement variation contributed by the operators and interactions between operators and samples. Process data was then linked to the MSA study, showing representative samples were selected and improvements to the measurement system could reduce hidden factory costs from over-processing and rework.
A case study on productivity improvement of wearing insert and cutting ringIJECSJournal
The objective of this paper is to present case study on a wearing insert and cutting ring for the efficient improvements in productivity with the help of various work Study Methods. In this study productivity is improved through identifying the process that involves the time required for the process as the main reason to achieve the objectives of increasing the productivity. Time and motion study is one of the necessary factors to set a standard target. The study is aimed at identifying the unwanted work processes which in turn increases the time required, efforts as well as the cost of the product. Thus the changes were made in the areas which require improving using work study methods.
Overview of 3 day Lean & Kaizen Course ContentTimothy Wooi
This document outlines the content of a 3-day Lean & Kaizen course. Day 1 covers topics like Lean Manufacturing principles, characteristics of Lean production including cellular layouts and Kanban systems. Day 2 focuses on standard work including takt time and pull production. Day 3 covers tools for standard work, Total Productive Maintenance (TPM), and Kaizen workshops which use small group projects to drive continuous improvement. The workshop method involves planning, implementing improvements on the production floor for a week, and follow up meetings to sustain results.
This project aimed to reduce paste usage and costs on Backing Line 4 by improving the calendar roll, backing roll, and installing new measurement tools. Goals included installing a new nip station, controlling paste temperature to manage viscosity, and using a Terahertz thickness gauge to eliminate destructive testing. The project achieved a cost savings of $1.7 million annually within one month by installing temporary new rolls. Controlling paste temperature and installing the gauge were ongoing. Success criteria included reducing paste usage and providing real-time thickness measurements for better process control.
The document provides information about fabrics finishing processes at Famkam Dyeing Ltd. It includes:
1. An introduction to fabrics finishing and its objectives.
2. Flow charts showing the finishing process and organizational structure.
3. Details of finishing machines including specifications.
4. Standard operating procedures and quality management systems.
5. Job responsibilities of finishing department staff.
6. Parameters for processes like heat setting and guidelines for chemical use.
Cover Story - China's Investment Leader - Dr. Alyce SUmsthrill
In World Expo 2010 Shanghai – the most visited Expo in the World History
https://www.britannica.com/event/Expo-Shanghai-2010
China’s official organizer of the Expo, CCPIT (China Council for the Promotion of International Trade https://en.ccpit.org/) has chosen Dr. Alyce Su as the Cover Person with Cover Story, in the Expo’s official magazine distributed throughout the Expo, showcasing China’s New Generation of Leaders to the World.
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product-review.ppt
1. 0
Right First Time Six Sigma Project
“Improve batch record system for Packaging ”
Start Date: 01 Feb 2008
Black Belt: Marina Suryanto
Sponsor: Sis Mardini (QO Manager)
Process Owner: Raharsih Basrodin (Production)
Team Members: Production: Lily, Yaseph, Lely
QA: S. Wigati, Yodi, Melissa
I-nexus ID: 3,031
2. 1
Control
Improve
Analyze
Measure
Define
The lead time to manufacture to release is too long.
Problem Statement
Business Case
Expected business results:
• Reliable supply of product
• Improve quality of records
• Reduce time and efforts needed to complete batch
documentation
3. 2
Scope
Control
Improve
Analyze
Measure
Define
The lead time to manufacture comprises of 2 parts i.e:
1. Raw material receipt to bulk film coated tablet and
final blend release (Project INX 7724 by JTM)
2. Primary packaging to product disposition
Product : Ponstan 500 mg Film Coated Tablet (FCT)
and Terramycin (TM) Oph. Oint.
START : Ponstan Blistering
TM Filling ointment
STOP : Product disposition by QA
Exclude : Batch with deviation and validation
4. 3
Project Goal
PROJECT GOAL METRIC BASELINE* CURRENT GOAL
Reduction of
packaging lead time
(LT)
Working Days Ponstan I:
Average 53
TM Oph II:
Average 26
TBD Ponstan*:
Max 20 days/
batch
TM Oph*:
Max 25 days/
batch
Control
Improve
Analyze
Measure
Define
I Data collected from lot released in Jul 2007 to Jan 2008.
II Data collected from lot released in Feb 2007 to Feb 2008
* Maximum exclude validation batch and deviation
5. 4
Control
Improve
Analyze
Measure
Define
Process Map
Packaging Flow of Ponstan 500 mg FCT (As Is)
Pack into Multicarton
Released
coated
tablets
Pack into Shipper
Folding Leaflet
Printing Multicarton
Folded
leaflet
Printed
multicarton
B
Yes
No
Blistering
Inspection on
defects
Export
product?
Pack into Export
shipper
6. 5
Control
Improve
Analyze
Measure
Define
Process Map
Batch Record Process of Ponstan 500 mg FCT (As Is)
TL calculate product
yield & accountability
B
TL
Completion in MAPS
by TL
Prod. Admin review
batch record for doc.
error
Yes
Admin
Prod Spv
Ok? No
TL/ Operator/
Inspector
Record data in the
log book of doc error
Prod Spv review and
sign off the batch record
Prod Manager
Prod Manager review
and sign-off the batch
record
Ok?
Yes
Yes
No
QA Spv review and
sign-off the batch
record
Quality Assurance
Profiles (QAP)
Ok?
Yes
Disposition in
MAPS
Ok?
Yes
Create CoA
QA Manager review
and sign-off the batch
record
Ok? No
Prod Manager/
Inspector/ Lab
Manager
No
Prod. Manager/
QA Spv
QA Spv
QA Manager
Review Batch record = Manufacturing + Packaging batch record
7. 6
Control
Improve
Analyze
Measure
Define
Process Map
Packaging Flow of TM Oph. Oint. (As Is)
Final
blend
Sampling for Lab
Test
Testing
Gamma radiation
Irradiated
products
Cartoning
A
Folding Leaflet
Printing
Multicarton
Folded
leaflet
Printed
multicarton
Packing for Gamma
radiation
Inspection on
defect
Yes
Inspection on
defect
Filling
Market: Korea?
Pack into
Shipper
No
Pack into
Multicarton
Shrink wrapping
Testing
Sampling for
Micro Test
Pack into
Shipper
8. 7
Control
Improve
Analyze
Measure
Define
Process Map
Batch Record Process of TM Oph. Oint. (As Is)
Review Batch record = Manufacturing + Packaging batch record
TL calculate product
yield & accountability
B
TL
Completion in MAPS
by TL
Yes
Admin
Prod Spv
Ok?
No
TL/ Operator/
Inspector
Record data in the
log book of doc error
Prod. Admin review
batch record for doc.
error
Prod Manager
Prod Manager review
and sign-off the batch
record
Ok?
Yes
Yes
No
QA Spv review and
sign-off the batch
record
Quality Assurance
Profiles (QAP)
Ok?
Yes
Disposition in
MAPS
Ok?
Yes
Create CoA
QA Manager review
and sign-off the batch
record
Ok? No
Prod Manager/
Inspector/ Lab
Manager
No
Prod. Manager/
QA Spv
QA Spv
QA Manager
Prod Spv review and
sign off the batch record
9. 8
Control
Improve
Analyze
Measure
Define
DATA PLOT PONSTAN 500 MG FCT
Total manufacturing lead time ranges from 59 to 99 days with median of 77 days.
Production process LT ranges from 17 to 37 days with median of 25 days.
Packaging to disposition LT ranges from 38 to 77 days with average of 52 days
which contributes 68% to the total LT.
Total Manufacturing LT = Production LT + Packaging to disposition LT
729-30164
729-30158
729-30152
729-30146
729-30137
729-30129
729-30123
729-30112
729-30099
729-30045
729-30038
100
90
80
70
60
50
40
30
20
10
Lot No
Days
Med: 25
Avg: 52
Med: 77
Production LT
Packaging LT
Total Manufacturing LT
Variable
Time Series Plot of Production LT, Packaging LT, and Total Manufacturing LT
10. 9
Control
Improve
Analyze
Measure
Define
DATA PLOT PONSTAN 500 MG FCT
729-30164
729-30158
729-30152
729-30146
729-30137
729-30129
729-30123
729-30112
729-30099
729-30045
729-30038
80
70
60
50
40
30
20
10
0
Lot No
Lead
Time
(Working
Days)
Med: 2
Avg: 50
Avg: 53
Packaging Lead Time
Final Review Lead Time
Total LT (Pack-Disposition)
Variable
Time Series Plot of Packaging, Final Review, and Total LT (Pack - Disposition)
Total lead time ranges from 38 to 77 days with average of 53 days.
Packaging process LT ranges from 1 to 12 days with median of 2 days.
Final review LT ranges from 35 to 75 days with average of 50 days
which contributes 94% to the total LT.
LT (Pack – Disposition) = Packaging LT + Final review LT
11. 10
Control
Improve
Analyze
Measure
Define
DATA PLOT PONSTAN 500 MG FCT
79% of the total review LT is contributed by the production review time.
Production review LT ranges from 26 – 58 days with average of 39 days.
QA review LT ranges from 1 – 28 days with average of 10 days.
Total Final Review LT
QA Review LT
Production Review LT
80
70
60
50
40
30
20
10
0
Days
38.8333
10.4833
49.5
Boxplot of Production Review LT and QA Review LT
12. 11
Control
Improve
Analyze
Measure
Define
DATA PLOT TM Oph. Oint.
Total Manufacturing LT = Production LT + Packaging to disposition LT
8-52001
7-52050
7-52042
7-52034
7-52030
7-52026
7-52023
7-52020
7-52010
7-52005
50
40
30
20
10
0
Lot No
Days
Med: 3
Avg: 27
Avg: 30
Production LT
Packaging LT
Total Manufacturing LT
Variable
Time Series Plot of Production LT, Packaging LT, Total Manufacturing LT
Total manufacturing lead time ranges from 2 to 7 days with average of 30 days.
Production process LT ranges from 14 to 45 days with median of 3 days.
Packaging to disposition LT ranges from 17 to 48 days with average of 27 days
which contributes 90% to the total LT.
13. 12
Control
Improve
Analyze
Measure
Define
DATA PLOT TM Oph. Oint.
Total LT ranges from 14 to 45 days with average of 26 days.
Packaging LT ranges from 6 to 21 days with median of 10 days.
Final review lead time ranges from 5 to 30 days with average of 16 days
which contributes 62% to the total LT.
8-52001
7-52050
7-52042
7-52034
7-52030
7-52026
7-52023
7-52020
7-52010
7-52005
50
40
30
20
10
0
Lot No
Lead
Time
(Working
Days)
Avg: 26
Avg: 16
Med: 10
Packaging LT_1
Final Rev iew LT_1
Total LT (Pack - Disposition)_1
V ariable
Time Series Plot of Packaging, Final Review, and Total LT (Pack - Disposition)
LT (Pack – Disposition) = Packaging LT + Final review LT
14. 13
Control
Improve
Analyze
Measure
Define
DATA PLOT TM Oph. Oint.
Production review time ranges from 1 – 18 days with average of 8 days.
QA review lead time ranges from 1 – 25 days with average of 8 days.
Total Final Review LT
QA Review LT
Production Review LT
30
25
20
15
10
5
0
Days
7.84375 8.125
16.0938
Boxplot of Production Review LT and QA Review LT
15. CAPABILITY ANALYSIS
14
Control
Improve
Analyze
Measure
Define
100% of the batches cannot meet the lead time of max 20 days.
Data is approx. normal
70
60
50
40
30
20
USL
LSL *
Target *
USL 20
Sample Mean 52.3
Sample N 60
StDev (O v erall) 6.89461
Process Data
Pp *
PPL *
PPU -1.56
Ppk -1.56
C pm *
O v erall C apability
% < LSL *
% > USL 100.00
% Total 100.00
O bserv ed Performance
% < LSL *
% > USL 100.00
% Total 100.00
Exp. O v erall Performance
Process Capability of Packaging Lead Time of Ponstan 500 mg FCT
16. CAPABILITY ANALYSIS
15
Control
Improve
Analyze
Measure
Define
40
32
24
16
8
USL
LSL *
Target *
USL 25
Sample Mean 26.6875
Sample N 32
StDev (O v erall) 8.05801
Process Data
Pp *
PPL *
PPU -0.07
Ppk -0.07
C pm *
O v erall C apability
% < LSL *
% > USL 50.00
% Total 50.00
O bserv ed Performance
% < LSL *
% > USL 58.29
% Total 58.29
Exp. O v erall Performance
Process Capability of Packaging Lead Time of TM Oph Oint
58% of the batches cannot meet the lead time of max 25 days.
Data is approx. normal
17. 16
Value Stream Map Analysis (Ponstan 500 mg FCT)
Control
Improve
Analyze
Measure
Define
Total Packaging Lead Time ranges from 24 – 29 days.
Total processing time (P/T) ranges from 3 – 3.5 days (23 – 26 hours)
Total delay time ranges from 21 – 26 days. Delay time was 89% of total LT
Processing time in batch record review ranges from 6 – 8 hours per batch with delay time
19 - 24 days. Delay time in review process needs to be minimized.
Note: Data taken from measurement of 3 batches
Printing
Multicarton
Folding Leaflet
Blistering
Completion
by TL
Review by
Production
Secondary
Packing
I
I I I I
Review &
Disposition by QA
Warehouse
Production -
Process
Warehouse
PT: 8 – 9 hours
LT: 1 WD
PT: 6 – 8 hours
LT: 1 WD
PT: 0.5 hours
LT: 1 WD
PT: 4 – 7 hours
LT: 17 - 21 WD
PT: 1 – 2 hours
LT: 2 - 3 WD
PT: 1.5 - 2 hours PT: 0.5 hours
0 WD
0
0 – 1 WD 2 WD 1 - 4 WD
18. 17
Value Stream Map Analysis (TM Oph Oint)
Control
Improve
Analyze
Measure
Define
Total Packaging Lead Time ranges from 22 - 33 days.
Total processing time (P/T) ranges from 15 – 18 days (113 – 134 hours )
Total delay time ranges from 6 - 15 days (45 – 113 hours). Delay time was 37% of total LT.
Processing time in batch record review ranges from 7 – 10 hours per batch with delay time
2 – 10 working days. Delay time in review process needs to be minimized.
Note: Data taken from measurement of 3 batches
Filling & Packing
for Radiation
8
I
Gamma
Radiation
Printing
carton
2
Completion
by TL
1
Review by
Production
3
Secondary
Packing
8
I
I
I
I I
Review &
Disposition by
QA
2
PT: 22.5 – 25 hours PT: 2 – 3 WD
Lab Testing
(Chem&Micro)
5
Production -
Process
Warehouse
Lab Testing
(Chemical)
2
Folding
Leaflet
1
0 - 2 1 - 2
Inspection on
defects
6
I
I
PT: 2 WD
0
PT: 4 - 5 WD
1 - 2
PT: 3.5 – 6 WH
0 - 5
PT: 6 - 9 WH
0 - 1
PT: 1.5 WH
LT: 3 WD LT: 3 - 4 WD LT: 5 – 6 WD
LT: 2 – 5 WD LT: 4 – 5 WD LT: 1 - 2 WD LT: 1 - 8 WD
PT: 7.5 – 8.5 hours
LT: 1 - 2 WD
PT: 4.5 – 7 hours
LT: 2 WD
Warehouse
PT: 2 hours PT: 14.3 hours
19. 18
Brainstorming
Why batch record review lead time is too long?
1. Structure and content of batch record is not user friendly/
complicated
2. Effort and time needed for correcting documentation errors
3. Flow of batch record review process is not efficient. Review level
that is labor intensive involving several personnel. The overall
documents of the batch record from manufacturing to packaging
is reviewed at the end of the process.
4. Standard lead time for batch record review and product release is
not clearly defined. Delay time during final review is high.
5. Batch record is accumulated waiting for review and sent to QA
including waiting time for approved QAP for TM Oph. Oint.
Control
Improve
Analyze
Measure
Define
20. 19
Batch record is accumulated waiting for review and sent to QA
Numbers of Batch Record sent to QA per month was variable
ranges from 1 – 23 batch records per receiving day with median of 5/ day.
Control
Improve
Analyze
Measure
Define
23-May-08
7-May-08
21-Apr-08
9-Apr-08
26-M
ar-08
10-M
ar-08
21-Feb-08
11-Feb-08
17-Jan-08
3-Jan-08
25
20
15
10
5
0
Date
No
of
Batch
Records
Med=5
Time Series Plot of No of Batch Records to QA per day
21. 20
Waiting time for QAP Availability
The QA review lead time, which ranges from 1 – 25 days, includes the waiting
lead time for QAP from lab. QAP LT ranges from -19 to 11 days.
Minus value means that the QAP has been received prior to the batch records sent to QA.
8-52004
7-52056
7-52049
7-52035
7-52031
7-52028
(MA
L)
7-52024
7-52021
7-52010
7-52005
30
20
10
0
-10
-20
Lot No
Days QAP LT
QA review LT
Variable
Time Series Plot of QAP LT & QA Review LT
QAP LT = Batch record receive date – QAP receive date
Control
Improve
Analyze
Measure
Define
22. 21
Improvement Matrix
Control
Improve
Analyze
Measure
Define
Potential X’s Proposed Solution Supporting Data
Structure and content of batch
record is not user friendly/
complicated: Excessive data
entries, excessive signatures,
Many separate forms are linked
to the batch record for data
recording.
Excessive data verification
during IPC between Production
and QA
Re-structure of batch record both
contents and format. The content is
also analyzed and some
improvements are made to comply
with PQS & regulatory
requirements.
Some of IPC activities and data
verification will be transferred from
QA to Production as per risk
assessment.
QA Risk assessment:
New IPC matrix:
Numbers of signatures for the
new format of batch packaging
records are reduced by approx.
50% (Ponstan FCT: 52%; TM
Oph: 58%)
23. 22
Improvement Matrix
Control
Improve
Analyze
Measure
Define
Potential X’s Proposed Solution Supporting Data
Documentation error - Re-structure batch record as above.
- Training Operator on documentation
practice for the new batch record
-
Flow of batch record review
process is not efficient. Review
level that is labor intensive
involving several personnel. The
overall documents of the batch
record from manufacturing to
packaging is reviewed at the end
of the process
New flow of packaging process
including IPC and batch record review
process:
- Batch record will be reviewed at each
defined stage.
- Reviewers include Prod Spv, Prod
Manager, QA Spv, QA Manager
Delete non-value-added activity i.e.,
Prod Admin function to check and
record doc error. These functions will
be integrated to all reviewers.
See proposal of new flow
in the next slides.
24. 23
Improvement Matrix
Control
Improve
Analyze
Measure
Define
Potential X’s Proposed Solution Supporting Data
Waiting time for approved QAP of
TM Oph Oint
The Lab Spv will also sign off the
batch record at each stage (Before
radiation & after radiation) to confirm
whether the test result meet or
doesn’t meet spec. The QAP will be
inserted into the batch record after the
Lab Spv sign off the BR at the after
radiation stage, then the batch record
will be circulated to the Prod and QA
Manager for final approval. This avoid
the delay due to QAP documentation.
-
Batch record is accumulated waiting
for review and sent to QA.
Define standard lead time for review:
1) Review at each stage: Max 1
business day per reviewer per batch.
2) Final review: : Max 2 business day
per reviewer per batch.
-
Standard lead time for batch record
review and product release is not
clearly defined. Delay time during
final review is high.
25. 24
Proposal for New Process Flow
Off-Line Printing
Printing
Examination & approval
of printed multicarton
sample
Verification by QA
Inspector
PM Reconciliation
Printing Inspection
Review dan approval
printing process by Prod
Spv
Batch packaging
records – Printing
stage
Warehouse Packaging
Line clearance
Printed
Multicarton
Multicarton
Control
Improve
Analyze
Measure
Define
26. 25
Proposal for New Process Flow
Folding Leaflet
Control
Improve
Analyze
Measure
Define
Folding
Examination & approval
of folded leaflet sample
PM reconciliation
Review dan approval
folding process by Prod
Spv
Batch packaging
records – Folding
stage
Warehouse Packaging
Line clearance
Folded
leaflet
Leaflet
27. 26
Proposal for New Process Flow
Filling & Packaging of TM Oph Oint 3.5 g Korea
Control
Improve
Analyze
Measure
Define
Final
blend
Compounding
Line Clearance Filling Packing for radiation
Inspection on defect
of filled alutubes
Gamma Radiation
Radiated
products
Inspection on
defect
Packing into carton
Packing into
Multicarton
Shrink wrapping
Packing into export
shipper
Finished
Products
PPIC
I
Examination &
approval of sample of
embossed empty tube
Verification by QA
Inspector
Start-Up
Inspection on filled
weight, foreign matter,
blend homogeneity,
and leak test
Inspection on
embossed lot no &
exp date End of Run
Check
Inspection on
defects
Sampling
Lab Testing
(Chemical)
Folded
leaflet
Printed
Multicarton
Sampling
Lab Testing
(Chemical & Micro)
Reconciliation
Batch record review
& disposition
Batch record review
and approval (Filling
stage)
A
B
Examination &
approval of
embossed carton
Inspection on
embossed lot no &
exp date
Start up (30 carton)
End of Run Check
(30 carton)
Weight monitoring
of carton,
multicarton, shipper
Verification by QA
Inspector
Inspection on
cartoning results
Examination &
approval of shipper
label
Inspection on product
& packaging defects
(ROI)
28. 27
Proposal for New Process Flow
TM Oph Oint 3.5 g Batch Record Review Process
Control
Improve
Analyze
Measure
Define
Yes
A
Ok?
Prod Spv
TL/ Operator/
Inspector
No
Prod. Spv review and
sign-off the batch
record
Lab Spv
Lab Spv sign off the
batch record
QA Spv
Ok? Yes
Prod Spv
No
Approved batch
packaging record
(filling stage)
QA Spv review and
sign-off the batch
record
Yes
B
Ok?
Prod Spv
TL/ Operator/
Inspector
No
Prod. Spv review and
sign-off the batch
record
Lab Spv
Lab Spv sign off the
batch record
Ok?
Yes
Prod Spv
No
Completion in
MAPS
TL/ Prod Spv
Production Manager
review and sign-off
the batch record
QA Manager review
and sign off the batch
record
Ok?
Prod Manager
QA Manager
Approved batch
packaging record Yes
No
Prod Manager
Disposition in MAPS
29. 28
Proposal for New Process Flow
Blistering & Packaging of Ponstan 500 mg FCT
Control
Improve
Analyze
Measure
Define
Coated
Tablet
Coating
Line Clearance Blistering
Finished
Products
PPIC
Examination &
approval of sample of
embossed empty
blister
Verification by QA
Inspector
Leak Test
Inspection on
embossed lot no and
exp date
Inspection on
blister defects
Printed
Multicarton
Batch record review
and disposition
Packing into
multicarton
Packing into export
shipper
Reconciliation
Examination &
approval of shipper
label
Folded
leaflet
Inspection on product
and packing defect
(ROI)
End of Run Check
Weight monitoring of
multicarton
Start-Up
A
30. 29
Proposal for New Process Flow
Ponstan 500 mg FCT Batch Record Review Process
Control
Improve
Analyze
Measure
Define
Yes
A
Ok?
Prod Spv
TL/ Operator/
Inspector
No
Prod. Spv review and
sign-off the batch
record
Ok?
Yes
Prod Spv
No
Completion in
MAPS
TL/ Prod Spv
QA Manager review
and sign off the batch
record
Ok?
Prod Manager
QA Manager
Approved batch
packaging record Yes
No
Prod Manager
Disposition in MAPS
Production Manager
review and sign-off the
batch record