Application of Measurement System Analysis at the ABC Company Asst. - - PowerPoint PPT Presentation

• Asst. Prof. Dr. Gökhan İZBIRAK

Supervisor Mohammad Khanjani Student

Application of Measurement System Analysis at the ABC Company

1

ISO 9001, ISO 14001, OHSAS 18001

Critical Part

1 Quality Planning

Miner non- conformit y

2

the purpose of this thesis

The performance level The need, requirements or expectation Time

S t a n d a r d

the degree to which a set of fundamental characteristics fulfils a need or expectation that is stated, generally implied or obligatory

• A degree of excellence
• Conformance with requirements
• The totality of characteristics of an entity that bear on its ability to

satisfy stated or implied needs.

• Fitness for use
• Fitness for purpose

“the degree to which a set of fundamental characteristics fulfils the requirements”

Quality

3

USL LSL

Target Japan United States

Montgomery (2005a) has defined quality term as a proportion to variability.

$

Japan US

Cost of Guarantee

This definition implies that if variability in the key characteristic of a product decrease, the quality of the product increases Real case: Transmission problem (US domestic plant and Japanese supplier)

4

Real case in IRAN: Honda motor company in Qhazvin city. About 8 years ago the managers decided to make one of the main parts in house, Shock absorber . After 2 years , they were successful to pass all of the testing requirements from Honda of Japan . But in the first try, all of the motorcycle were claimed by the customer, Why? The claim reports base on the customer voice : the flexibility is high the flexibility is low A team conducted survey and they took 200 samples from the original Shock absorber that have been assembled to the motorcycle before from the market .

5

The performance indicators of Dell show that this company manufactures more than 50,000 computers every day, but carries only four days of inventory (competition carries 20–30 days). From quality issues point of view Dell launched the Critical Supplier Partnership Program resulting in improvement in quality metrics and continuity of supply. This program reduced early field failures by 37% and manufacturing line failures fell from 15,000 to 3000 defective parts per million (dppm) PIONEERS OF SCQM

6

The automotive industry is the biggest industry in the world. Advanced Product Quality Planning (APQP) Measurement System Analysis (MSA) Statistical Process Control (SPC) Failure Mode and Effective Analysis (FMEA)

AIAG

Automotive International Action Group

Part product approval process (PPAP)

7

The purpose of this thesis is to find a solution for improvement of the controls

among the product realization in designer and manufacturer of the gas turbine blades with applying the two Automotive Supply Chain tools which are known as Measurement System Analysis (MSA) and Advanced Product Quality Planning (APQP) This idea is taken from works of Carol J. Robinson et al. (2004) in which illustrate the Supply Chain Quality Management characteristics and works

• f M. Bobrek et al. (2005) in which investigate the APQP model in other

sectors as a basic concept for designing and implementation of Integrated Management System (IMS)

8

QUALITY IN THE SUPPLY CHAIN MANAGEMENT Developing and maintaining strong relationships between firms and their suppliers, as well as among suppliers at different layers of the supply chain, has become an important strategic issue. Many have suggested that supply chain management can lead to faster product development, decreased production lead-times, reduced cost, and increased quality (Choi. T. Y, 1999). Tan et al. (1999) conducted a survey on quality directors and vice- presidents from a broad range of industries, and concluded that successful management and well-defined linkages between Total Quality Management (TQM) practices and performance is the key to long-term success. In addition, they concluded that many strategic quality approaches and Supply Chain Management tools are positively correlated with firm performance.

9

Some of the related questions which supported this idea are:

• Training in basic statistical techniques such as histograms and control charts.
• Training in advanced statistical techniques (design of experiments and

regression).

• Quality awareness provided to managers and supervisors.
• Development of procedures for monitoring key indicators of competitor and

customer satisfaction performance.

• Quality department plays an active role in providing specific training such as

Variation concepts and SPC. Carol J. Robinson, et al. (2004) conducted a comprehensive review in quality management system among SCM and provided a new definition for it as Supply Chain Quality Management (SCQM).

10

• Acceptance

Sampling

• Control charts
• Statistical quality

Control

• Inspection
• Zero defects
• Program solving
• Quality circles
• SPC
• DOE
• TQM
• ISO9001
• Baldrige Award
• Six-sigma

Supply Chain Management Supply Chain Quality Management (SCQM) 11920-1960 Internal Organization 1960-1980 Internal Organization 1980-1990

• Supply-base
• Organization
• Customer exception

1990-present All supply channel members and mostly internal organization 2004-present All supply channel members and mostly external organization Programs Years Focus

Traditional quality programs focusing on approaches such as TQM, the Malcolm Baldrige National Quality Award (MBNQA) and ISO 9001 (international quality management system standard), must now transform to a supply chain perspective in order to simultaneously make use of supply chain partner relationships and quality improvement gains essential to marketplace satisfaction. A case study of a firm that is a first-tier supplier in an automotive supply chain is presented to better illustrate the SCQM themes and their treatment in industrial practice. Information for this case study was gathered during ISO 9001:2000 pre-assessment auditing and a detailed structured interview with the Assistant Vice President of the firm.

11

SCQM evolution

For many firms, obtaining acceptable levels of quality starts with the registration of a QMS for itself and its suppliers to ISO 9001. From reliability (how often does the product fail?) point of view, J. D. Booker et al. (2001) argued that, reliability prediction will remain a debatable technique until the statistical methods for quantifying design parameter becomes embedded in everyday engineering. Attention needs to be focused on the quality and reliability of the design as early as possible in the product process development. A lack of understanding of variability in manufacturing and service conditions at the design stage is a major contributor to poor product quality and reliability To communicating reliability problem: FMEA, QFD, DOE Quality Assurance registration does not necessarily ensure product quality, but gives guidance on the implementation of the systems needed to trace and control quality problems (Robert et al., 2007).

12

APQP

Control Sheet Control Sheet Control Sheet Control Sheet Control Sheet Control Sheet Control Sheet Control Sheet

The goal of Product Quality Planning (PQP) is to with everyone involved to assure that all required steps facilitate communication are completed in time (M. Bobrek a. et al., 2005).

13

Advanced Product Quality Planning (APQP) (a) Organize the team (b) Define the scope (c) Team-to-team (d) Training (e) Customer and supplier involvement (f) Parallel engineering (g) Control plans (h) Concern resolution

14

Most of the application of APQP has been used for production process in the manufacturing industry by many researches. First significant application

• f APQP in integrated management system (IMS) design has been

employed by M. Boberk et al. (2005) This model as a procedure has been tested on over the 30 certified quality management systems and 2 environmental management systems. Integrated Management System: ISO 9001+ISO 14001+OHSAS 18001

15

PLAN DO STUDY ACT PLAN DO STUDY ACT PLAN DO STUDY ACT 1- ANALYZE THE PROCESS

• What should the process be

doing?

• What can go wrong?
• What is the process doing?
• Achieve a state of statistical

control

• Determine capability

2- MAINTAIN THE PROCESS

• Monitor process

performance.

• Detect special cause

variation and act upon it. 3- Improve the process

• Change the process to better

Understand common cause variation.

• Reduce the common cause

variation

The process improvement cycle

• 1. Basic understanding of the process among identifying common and

special causes and achieving a state of statistical control.

• 2. Due to processes are dynamic and will change, the performance of

the process must be monitored with effective measures. 3.To covering the customer needs which are sensitive to excessive variation within engineering specification, additional process analysis tools, including more advanced statistical method such as designed for experiment (DOE) and advanced control charts (such as cumulative control chart) may be useful in the third stage.

16 1 2 3

The immediate objective of Six Sigma is defect reduction. It has a process focus and aims to call attention to process improvement opportunities through systematic measurement (Mahesh S. et al. 2005). Six Sigma and APQP Stamatis (2000) argued that organizational culture needs to put quality into planning and drive quality throughout the entire

• rganization.

He states that Six Sigma reformulates the quality operating system introduced by Ford Motor Company in the early 1990s. The APQP method alone, Stamatis believes to be superior to Six Sigma

17

MEASURMENT SYSTEM ANALYSIS The traditional approach to the management of the measurement process is calibration. calibration is done under controlled environment and by specially trained personnel On the shop floor, where these instruments are used, the measurement process is affected by the factors like

• method of measurement,
• appraiser’s influence,
• environment,
• work piece.

Observed value = True value + Measurement Error managing "measurement error," generally called Measurement Systems Analysis (MSA), is an extremely important function in process improvement (Montgomery, 2005a).

Actual process variation Observed process variation Production gage variation 18

            

2 2

3 , 3 min

d R d R pk

LSL X X USL C    

2

6

d R p

LSL USL C    

LSL Target USL

19 6 

p

C 1 

pk

C

if Cp Cpk

• ff-center Special causes

If the measurements are all “close” to the master value for the characteristic, then the quality of the data is said to be “high.” (AIAG, MSA, 2002).

20

Repeatability and Reproducibility Repeatability is the variability of the measurements obtained by one person while measuring the same item repeatedly Reproducibility is the variability of the measurement system caused by differences in operator behavior. Mathematically, it is the variability of the average values obtained by several operators while measuring the same item with the same instrument Possible causes for poor repeatability:

• within part (form, position, surface, taper, sample consistency), within

instrument (repair; wear, equipment or fixture, poor quality or maintenance),

• within method (variation in setup, technique, holding, clamping),
• within appraiser (technique, position, lack of experience),
• within environment (short cycle fluctuations in temperature, humidity,

vibration, lighting, cleanliness or wrong gage for the application

21

Repeatability

Potential sources of reproducibility error:

• between parts (average difference when measuring type of parts A, B, C, etc.

using the same instrument, operators, and method),

• between instruments (average difference using instruments A, B, C, etc., for

the same parts, operators and environment),

• between appraisers (average difference between appraisers A, B, C, etc.,

caused by training, technique, skill and experience.

22

Range & Average Method (AIAG, MSA)

The Range & Average Method computes the total measurement system variability, and allows the total measurement system variability to be separated into repeatability, reproducibility, and part variation The recommended method is to use 5 parts, 2 appraisers and 3 trials, for a total of 30 measurements.

23

2

15 . 5 d R V

p p 

      TV R GR & %GR&R = 100

2 2

ility reproducib ity repeatabil 

GR &R = nr ity repeatabil d X range

2 2 2

15 . 5          Reproducibility =

2

15 . 5 d R  Repeatability GR&R Percentage Measurement system Less than 10% Acceptable 10% to 30% May be acceptable based on importance Of application, gage cost, etc. More than 30% Unacceptable-measurement System needs improvement

      R GR V p &

ndc = 1.41

• 5 or more, the measurement system is interpreted as good,
• between 2 and 4 is conditional (i.e. the final judgment is based on if

the characteristic behavior define the safety or regular requirements if not, it is not accepted),

• less than 2 is unacceptable (it is interpreted as go/no go gage).

2 2

&

p

V R R TV  

24 %GR&R Actual process Cp Observed process Cp 10 2.0 1.96 30 2.0 1.71 60 2.0 1.2

Analysis of the Variance Method application in MSA

ijl ij j i ijl

R PO O P y      ) ( 

E

MS ity repeatabil 15 . 5  bn MS MS ility reproducib

AB A 

 15 . 5 abn Y bn Y SS

a i i A 2 1 2 ..)

(

   

   abn Y an Y SS

b j i B 2 1 2 . . )

(

   

  

B A b j ij a i AB

SS SS abn Y n Y SS    

     



2 1 2 . 1

) ( abn Y Y SS

b j n k ijk a i T 2 1 1 2 1      

 

 

B A AB T E

SS SS SS SS SS     n MS MS I

E AB 

 15 . 5

2 2 2

& I ility reproducib ity repeatabil R R    an MS MS V

AB A P

  15 . 5 25



Tsai’s (1989)

Stability is the total variation in the measurements obtained with a measurement system on the same master or parts when measuring a single characteristic over an extended time period (without any changing in operator, instrument, method and sample) Stability

• Instrument needs calibration with reducing of calibration interval.
• Worn instrument, equipment or fixture.
• Poor maintenance- air, power, filters, rust.
• Worn or damaged master, error in master.

R D UCLR

4

 R D LCLR

3

 R A X UCLX

2

  R A X LCL X

2

 

2

6

d R g

LSL USL C    

            

2 2

3 , 3 min

d R d R gk

LSL X X USL C     26

Burr (1967): comments that the usual normal theory control limits constants to the and can be employed unless the population is extremely non-normal. Montgomery 2005a: the role of theory and assumption such as normality and independence is important to have reliable limits for the sake of monitoring the process performance, but plays a much less important role in the application of Xbar and R chart which is considered as trial control limits. Arguments on the Normality assumption

27

Advanced Product Quality Planning and Measurement System Analysis Obviously, planning is the key stage before designing and purchase of measurement equipment or systems. The teams of individuals that will employ and be responsible for the maintenance and continual improvement of the measurement process have direct responsibility for developing the detailed concepts of MSA and this can be part of the APQP team efforts.

28

SYSTEM IDENTIFICATION AND PROBLEM STATEMENT A case from a company (ABC Technology) located in south-eastern region of Iran is presented in order to illustrate the problem and also to explore the application of MSA in controlling and managing of quality planning in a better way ABC company XYZ company

29

Organization Structure Project Characteristic

Functional Weak Matrix Balanced Matrix Strong Matrix Projectized Project Manager’s Authority Little or None Limited Low to Moderate Moderate To High High to Almost Total Resource availability Little or None Limited Low to Moderate Moderate To High High to Almost Total Who controls the Project budget Functional Manager Functional Manager Mixed Project Manager Project Manager Project Manger’s Role Part-time Part-time Full-time Full-time Full-time Project Management Administrative Staff Part-time Part-time Part-time Full-time Full-time

Structure of the ABC company (current cases for the company are underlined)

30

As a global approach, major company (XYZ) wants their partners (ABC Company who is one of their main suppliers) to implement and register to the ISO 9001, ISO 14001 and OHSAS 18001 and then, continual improvement of the related process performance.

Maintenance of the certificate

In the case of ABC, the company has been registered to ISO 9001 from 2002 and IMS recently, the history of the related record such as the reports of the certification body present that the number of minor non-conformities, still remains to be solved

ISO 9001: Requirement 7.3.1 (see Appendix A). In some case, the stages of the design and development review, verification and validation has not been covered as consequently. ISO 9001: Requirement 4.1 (see Appendix A). Defined measures for engineering and design process are not sufficient for effective monitoring and measuring of the quality parameters. ISO 9001: Requirement 8.4 (see Appendix A). In some cases, the data records of the ABC company have not been utilizing to identifying improvement opportunity properly. ISO 14001: Requirement 4.3.1 (see Appendix A). In some cases, the ABC company has not been considering the environmental aspects and related potential risk requirements in the product planning stage.

Continual improvement of the quality management system

Managemen t responsibility Measurement, analysis, and improvement Resource managemen t Product realizatio n

Customer s

Requirem ents Inp ut

Customer s

Satisfact ion

Outp ut Produ ct

31

Current process planning at the ABC company For the controlling of the product realization stages the product design department of ABC Company define the process planning sheet, relevant check lists and instruction. According to the subjected product model in this study, 14 inspection stages with relevant checklists are requested by the process planning sheet. For instance, in the dimensional control stage (which is before the polishing

• peration) 17 parameters are defined for measuring (such as dial, height,

maximum feeler, twist and etc) This form format of checklists lacks the required and considered form benchmarking control plan as suggested by the AIAG, APQP, 2002.

32

• 1. Two different operators use the gage to obtain replicate measurements
• n units.
• 2. Obtaining a 5 sample parts that represent the actual or expected range
• f process variation. (i.e., sample parts have not been chosen in a flash

from manufacturing process

• 3. Two candidate operators have been qualified for applying of the gage.
• 4. The set of gage has been calibrated by the authorized department

before Assumptions (GR&R)

33

• 5. During the examination the identification numbers of parts are not visible to

the appraisers.

• 6. To reducing of environment effect during of study, GR&R started and

continued for two appraisers without any interruption

• 7. The condition such as gage, method, examiner and sample parts are

equal for two appraisers.

• 8. During of the study, supervisor of the examiner has not authorized to butt

in measurement process

• 9. During of the study, just one of the two appraisers is ready in the place.
• 10. The resolution of the gages is 0.01 (i.e., the equipment is capable to

read a change of 0.01 it is mean the general rule of thumb which says “the measuring instrument discrimination ought to be at least one-tenth of the range to be measured ” is satisfied).

• 11. In this experiment the first error type is equal to 0.05%.

34

• The instrument needs maintenance.
• The gage may need to be redesigned to be more rigid.
• The clamping or location for gaging needs to be improved.
• There is excessive within-part variation.

Numerical results (Xbar and R method)

35

When reproducibility is greater than repeatability:

36

Furthermore, throughout the experiments we observed that fitting the parts into the gage is associated with a great difficulty. Due to lack of automatic resting of parts into the gage, both ends of parts (left end and right end) should be held by human operators and in this case, locking the levers becomes only possible if one of these two different method are used, a) using a chin or b) assistance provided by another human operator.

Source DF SS MS F P PART 4 0.0049200 0.0012300 0.18053 0.937 OPERATOR 1 0.0000300 0.0000300 0.00440 0.950 Part * Operator 4 0.0272533 0.0068133 9.92233 0.000* Repeatability 20 0.0137333 0.0006867 Total 29 0.0459367

Reproducibility is 86.51% is large compared to repeatability with 50.16%, and the possible causes could be Claim: The main problem comes from fixture design. ANOVA method (D3 characteristic)

37

PART Average 5 4 3 2 1 8.0 7.5 7.0 6.5 6.0

O PERA TO R 1 2

OPERATOR * PART Interaction Gage R&R (Xbar/R) for D1

PART Average 5 4 3 2 1 6.2 6.0 5.8 5.6 5.4 5.2 5.0 4.8

OPERATOR 1 2

OPERATOR * PART Interaction Gage R&R (Xbar/R) for D2 OPERATOR 2 1 8 7 6 5 4

D1 by OPERATOR

Gage R&R (Xbar/R) for D1

OPERATOR 2 1 6.5 6.0 5.5 5.0 4.5 4.0 3.5 3.0

D2 by OPERATOR Gage R&R (Xbar/R) for D2

Graphical results:

38

OPERATOR 2 1 5.975 5.950 5.925 5.900 5.875 5.850 5.825 5.800

D3 by OPERATOR

Gage R&R (Xbar/R) for D3

OPERATOR 2 1 6.5 6.0 5.5 5.0 4.5 4.0

D4 by OPERATOR

Gage R&R (Xbar/R) for D4 PART Average 5 4 3 2 1 5.92 5.90 5.88 5.86 5.84 5.82

O PERA TO R 1 2

OPERATOR * PART Interaction

Gage R&R (Xbar/R) for D3

Graphical results (Count.)

39

PART Average 5 4 3 2 1 5.0 4.8 4.6 4.4 4.2 4.0

O PERA TO R 1 2

OPERATOR * PART Interaction

Gage R&R (Xbar/R) for D4

40

Assumptions related with Stability are:

• 1. The set of the gage has been calibrated by the authorized department and

their certificates exist.

• 2. Due to lack of existing of reference value(s) relative to a traceable standard, a

production part that falls in the mid-range of the production measurements has been selected (this part is known as master part).

• 3. The experiments doing under controlled and protected environment.

lack of gage design or calibration performance.

(one qualified operator, and one master part in interval times)

Sample Mean 10 9 8 7 6 5 4 3 2 1 5.57 5.56 5.55 _ _ X=5.5604 UCL=5.57285 LCL=5.54795 Sample Range 10 9 8 7 6 5 4 3 2 1 0.04 0.02 0.00 _ R=0.02158 UCL=0.04563 LCL=0 Sample Values 10 8 6 4 2 5.56 5.54 5.52 5.58 5.57 5.56 5.55 5.54 5.53 5.52 5.58 5.56 5.54 5.52

Within Overall Specs

Within StDev 0.00928 C p 21.56 C pk 1.42 C C pk 21.56 O v erall StDev 0.00952 Pp 21.02 Ppk 1.39 C pm *

1

Process Capability Sixpack of master D2

Xbar Chart R Chart Last 10 Subgroups Capability Histogram Normal Prob Plot A D: 4.342, P: < 0.005 Capability Plot Sample Mean 10 9 8 7 6 5 4 3 2 1 4.41 4.40 4.39 _ _ X=4.4006 UCL=4.41376 LCL=4.38744 Sample Range 10 9 8 7 6 5 4 3 2 1 0.04 0.02 0.00 _ R=0.02281 UCL=0.04824 LCL=0 Sample Values 10 8 6 4 2 4.42 4.40 4.38 4.42 4.41 4.40 4.39 4.38 4.425 4.410 4.395 4.380

Within Overall Specs

Within StDev 0.00981 C p 20.39 C pk 6.78 C C pk 20.39 O v erall StDev 0.01044 Pp 19.17 Ppk 6.37 C pm *

Process Capability Sixpack of master D4

Xbar Chart R Chart Last 10 Subgroups Capability Histogram Normal Prob Plot A D: 1.893, P: < 0.005 Capability Plot

Stability – final judgment about gage performance

41

Some suggestions have been offered to help the improvement of the current quality planning and resolving of the non-conformities which arise from Integrated Management System requirements at the ABC company. 1.To satisfy of the expectations and requirements of the current IMS as well as establishing lines of communication with other internal and external customers and suppliers, the APQP team member should be arranged. Then, these requirements should be formed as checklist to assure that if the relevant needs (such as: ISO 14000 requirements) are not met then, the next stages will be limited. Moreover doe to, the projects managers will contrast with the new forms, it is suggested that this requirement merged in the currents quality planning and checklists.

• 3. Since the success of an APQP is dependent upon an effective training

program, then some courses emphasizing on the variation, capability, measurement errors, PDSA concepts should be defined and developed in ABC Company DISCUSSION OF THE RESULTS AND CONCLUSION

42

• 2. The key characteristic should be defined in c.plan. identifying of the key
• r critical parameters help the control to focus the efforts on the essential

demands like safety.

• 4. During the planning and execution of the project, the team will encounter

product design and/or processing concerns (such as: excess GR&R, non- conformities which arise from internal or external auditing based on the ISO9001

• r ISO14001). These concerns should be documented on a matrix with assigned

responsibility and timing. Disciplined Problem-solving methods (such as 8D) are recommended in difficult situations (see Appendix I).

• 5. In order to evaluation of APQP team efforts, the %GR&R and other related

trends should be reported regularly. This result not only could be used as an indicator (ISO 9001: 4.1 requirement) but also as a statistical tool could be utilized for verification of design stages. A sample of MSA plan which has been included to the Chapter H could be considered as part of the proposed APQP.

Characteristic Specification Ranking & Source Instrument & Resolution Study date GR&R Action plan # Thickness 4+,- 0.1 A FMEA#035 Micrometer 0.01 26.2.2009 60% 02 Diameter 6+,- 0.5 B SPC(2.2.2009) Caliper 0.1 26.2.2009 29% 03

43

• 6. In order to identify the potential risk of the designed or modified product and

improvement of the team working performance, the Failure Mode and Effect Analysis (FMEA) is suggested. To illustration the relationship between the FMEA with other tools and specific customer requirements (Q101 term indicate the specific requirement of the Ford company.), Appendix H has been included to this thesis. Meanwhile, the Figure H.1 could be considered as the sample of the procedures which describes the APQP methodology clearly.

44

Does customer feedback suggest control plan changes? Are operating And SPC procedures sufficient to make control plan work? Are preventive process actions identified? Is the quality system Ford approved? Have characteristics for sensitive process been identified for SPC? Can control charts for variables be Used on all key characteristics? Is the process ready for sign-off ? Is 100% inspection required? Does the plan have customer concurrency? Can product be manufactured, Assembled, and tested? Are engineering changes required?

• Repair rate objective
• Repair cost objective
• Field concerns
• Plant concerns

Q101 quality system Feasibility analysis

• process/inspection flowchart
• process FMEA
• Floor plan
• Historical warranty quality analysis
• New equipment list
• Previous statistical studies
• Design of experiments
• Cause-and-effect diagram

Can causes of field plant concerns be monitored? Manufacturing control plan

• Quality system/procedures
• Key process/product characteristics
• Sample size/frequency
• Inspection methods
• Reaction plan
• Statistical methods
• Problem-solving discipline

Process potential study

• Statistical training
• Implementation
• Results

Process sign-off

• Process sheets
• Inspection instructions
• Test equipment/gauges
• Initial samples
• Packing

Are process changes needed to improve feasibility? Job # 1 Ford Motor Company Never-ending improvement Has a launch Team been Identified? Was the process FMEA used to develop Process sheets? Quality planning team Supplier quality assistance Supplier or customer product engineering Warranty responsible activity

FMEA interrelationships

45

Base on the result of this study replicating this study in the same system or

• ther sector, using MSA, APQP and FMEA methodology may be added to

ranking (prioritizing) the potential risk. Argument which has been developed

• n the GR&R may be helpful for future investigations / research.

Feature work

46

Thank you

47