University of Rome Tor Vergata - summerschool-aidi.it

Measuring and Improving Manufacturing plant performances: Development and Dissemination of a customized Model for the

Italian Industrial Laundry Sector

University of RomeTor VergataDepartment of Mechanical Engineering,Industrial Engineer Research Group

Vittorio Cesarotti, Alessio Giuiusa, Vito Introna

University of Rome, “Tor Vergata”14 september 2011

“XVI Summer School Francesco Turco”

Vittorio CesarottiAlessio GiuiusaVito Introna

Table of Content

• The Context

• Introduction of Measurement System

• Benchmarking and dissemination

• Conclusions and further Research

2







Table of Content

• The Context




3







Introduction

Indicators

Tecniques

Methods

PrinciplesO

p

eratio

n

s

M

an

ag

em

en

t

S

p

ecific

In

d

u

strial S

ecto

r

Firm History Industrial Sector Product Process




Introduction

MultinationalCompanies Human Resource

SMEs Lack of Industrial Culture and HR University Support

Industrial Culture

ItalianIndustrial

Laundry Sector

Others companies





•More than 600 companies

•Turnover higher than 1,8

Billion €/year

•25.000 Employees(*) www.eblinazionale.it

In

vestm

en

t

in

A

u

tom

ation

2001 2010Year

Facilitate natural process

Accellerate Growth of Industrial Culture







Project Phases and Deliverables

PHASE 1:

•analysis of laundry industrial plants •design of a measurement system

PHASE 2:

•Dissemination•Benchmark

Guidelines for Measurement System Implementation

Plan of DisseminationBenchmark tool




Table of Content

• The Context




8







Key Performance Indicators

“Key Performance Indicators (KPIs) represent a set of measures focusing on those aspects of organizational performance that are the most critical for the current and future success of the organization” (Parmenter, 2010).

Data Collection

EffortBenefitsReward

Monitoring of KPIs requires a big effort due to data collection, therefore it must be abundantly rewarded by the benefits obtained through their use. (George, et al., 2005)

Key Performance Indicators must be effective for all the Laundries within the sector




Textiles

M

achinery

U

tilities

H

um

an

Resource

OverallProduction Plant Productivity


Sample Selectionwithin Assosistema

SurveyIdentification of

the Production Key Factors

If you can not measure it, you can not improve it. (Kelvin, 1900)

•Goal

•Definition

•Formulation

•Frequency of detection





BasicIndicators

BasicIndicators

First LevelIndicatorsFirst LevelIndicators

Second LevelIndicators

Second LevelIndicators

Laundries not accustomed to industrial performance system or to data collection.

They can provide more information about the first level indicator behavior and can help in analysis for improvement.

Information on identified areas




Machinery Textiles

Machinery

Utilities

Hum

an

Resource


Machinery Capacity

textiles mix: napkins, tablecloths, towels, sheets, etc.

HR assignment

excessive and uncontrolled shifting of operator from one to othermachinery can determine a reduction of machinery productivity

Productivity of machineries depends directly to the number of allocatedoperators.HR can be reallocated easily to different machineries depending onthe priorities of production




Machinery Textiles

Machinery

Utilities

Hum

an

Resource


Theoretical Capacity

Practical Capacity

Actual Capacity

Machineryinefficiencies

Unplanned sub utilization

Established Mix, Ideal Condition: No Machinery Losses, No change in HR Location

Established Mix, Real Condition: Machinery Losses, No change in HR Location

Established Mix, Actual Condition: Machinery Losses, Unplanned sub utilization due to HR Location




Textiles

Machinery

Utilities

Human

Resource


KPI Definition Scope - PurposeMixTheoreticalProductiveCapacity

Amount of daily deliverable textiles, for a a certain textile mix, for aplanned production period, with the maximum use of machinery(using all the time scheduled for production with actors in full) inTheoretical production conditions ( then without loss of capacity dueto inefficiencies that occur during production). It is a function ofproduction speed and the mix of daily time in which it is planned toproduce, called time load.

Evaluate the theoretical machineryperformance in terms of produced quantityof textiles, for a chosen mix, which could beprocessed every in absence of productioninefficiencies.

MixPracticalProductiveCapacity

Amount of daily produced textiles, with a chosen textile mix, actuallyprocessed in real conditions. It consider both the actual effective useof the machinery and the total amount of capacity losses that occurduring production.

To evaluate the actual practical (real)performance of the machinery, in terms ofamount of daily processed textiles for thechosen textile mix with actual realmachinery usage conditions.

Mix ActualProductiveCapacity

Amount of textiles, for a chosen mix, processed in one day using themachinery during all the scheduled time for production(with all HRavailable) but in real conditions. It take into account the total amountof capacity losses due to the inefficiencies that occur during the dailyproduction .

To evaluate the real performance of themachinery in terms of amount of textiles fora chosen mix that could be daily processedconsidering the total amount of capacitylosses.

Planningfactor

The ratio of: Production scheduled time (load time) and solar time forwhich is available our machinery. It’s expressed in percentage terms.

Assess the proportion of machinery that thecompany choose to use only for a certainperiod of time (load time) within the entireavailable time period (solar time of 24 h /day).

Utilizationfactor

Estimating the proportion of actual productive capacity that is used.It take into account any reductions in capacity for the specific needsof work adjustment (such as interruptions in production and / orproduction periods at reduced speed due to the reduction in thenumber of operators ).

The ratio between actual capacity andtheoretical productive capacity. it isexpressed in percentage terms.

OEE Evaluate the performance of the system in terms of efficiency. Thepossibility to exploit the theoretical productive capacity, holdingcapacity losses due to production inefficiencies such as equipmentfailure, delays or stops unwanted, minor stoppages.

The ratio between the practical productivecapacity and theoretical productivecapacity. It is expressed in percentageterms.

Machinery




Textiles

Machinery

Utilities

Hum

an

Resource


TextilesThe purpose of textile productivity is to measures the laundry ability to obtain the best result by their investment in textile resources

Ensure the longest life possible in accordance with textile quality standards

Minimizes the time when the textile is stocked therefore unutilized,.

Quality due to the processQuality due to abnormal use of textiles by Customer




KPI Definition Scope - Purpose

TextileUseful life

The textile average useful life is the ratio (for aparticular type of head and a given period of time)between the amount of processed textile and theamount of new textile put into production system inorder to replenish the initial quantity which tends todecrease for various reasons

Estimate the average useful life ofown textiles in terms of averagenumber of washes.

TextileRotationIndex

The textile rotation index is the relationship between theamount of textile processed in a given time period andthe amount of textile supplied to customer for the sameperiod.

Provide an average of the number oftimes that a single cloth is processedin one month. It allows to assess thecorrect rotation of the textiles clothand to identify abnormal situationssuch as the presence of excessivestocks.

Textileamongcustomer

It is the percentage of textiles back fromthe client without any obvious damage orneed for special washing.

Assessing the correct use of textilesby the customer, highlightingpotential abnormal uses abnormalthat lead to a premature end of thetextiles life.

Textiles

Machinery

Utilities

Hum

an

Resource


Textiles




Textiles

Machinery

Utilities

Human

Resource


Human Resources

KPI Definition Scope - PurposeHRProductivity

The relationship between the amount of processed textiles by the plant and the total hoursof paid labor.

The company's ability totransform the paid hours of its HumanResources into processed in textiles.

Direct HRYield

It is the ratio between the total amount oftextiles processed by a machinery and the totalnumber of hours worked in that machinery bydirect HR for that textile production.

Evaluate the ability to transform thehours worked by staff directly involved inthe of the production process in amountof laundry processed.

Indirect HRYield

The ratio between the hours worked by indirectHR and hours globally worked by all employees.

Assess the percentageimpact of total hours worked by all HR

Overtimeimpact

It is the ratio between overtime and the totallabor hours paid. It is expressed in terms ofpercentages.

Assess the impact of overtime work incomparison with the total work.

average cost per hour worked in Human Resources

ability of the company to process as much

possible textile per hour worked

The productivity of human resources measures the ability to get the best result (amount of laundry processed daily) from staff who daily work in the plant (total

hours of work or cost total staff).




Textiles

Machinery

Utilities

Hum

an

Resource


Utilities

Under the term "utilities" are grouped as the main energy resources, necessary for the operations of the production process. Utilities are eventually converted and distributed to the various production units where the utilities are transformed into useful work (Fawkes, 2007) through utility systems (electric, water plant, etc..).

KPI Definition Scope - PurposeElectricalProductivity

The ratio between the amount of the processedtextiles by the plant in a month and the totalconsumption of electricity for the same period.

Evaluate the ability to transformelectrical energy into processedtextile.

Gas Productivity The ratio between the amount of the processedtextiles by the plant in a month and the totalconsumption of gas for the same period.

Evaluate the ability to transform thegas resource into processed textile.

Oil Productivity The ratio between the amount of the processedtextiles by the plant in a month and the totalconsumption of oil for the same period.

Evaluate the ability to transform theoil resource into processed textile.

WaterProductivity

The ratio between the amount of the processedtextiles by the plant in a month and the totalconsumption of water for the same period.

Evaluate the ability to transform thewater resource into processedtextile.

EnergeticResourceProductivity

The ratio between the amount of the processedtextiles by the plant in a month and the totalconsumption of all energetic resources (electricity,gas, oil and water) for the same period.

Evaluate the ability to transform theenergetic resources into processedtextile.




Analysis and ImprovementANALYSIS TOOLS IMPROVEMENT TECNIQUES

X = The tool should be used for KPI analysis

○ = The technique can be used to improve the KPI

●= The technique can be used to strongly improve the KPI

Key Performance Index Cause

-effect diagram

Correlation Diagram

Data Stratification

Histogram

Pareto Chart

Run Chart

5 W

hys

5S Autoproduction

Custom

er involvem

ent

Ergonom

ics

Good Process Adjustm

ent

Good production planning

HR m

otivation and

HR Responsibility

Internal logistic

Job Rotation

Maintenance

New Technologies

Production activities

Production Planning

Reduction in energy

Reduction Theoretical

SMED

Suppliers selection

Mix Theoretical Capacity x x ○ ○ ○ ● ● ○ ● ○Mix Actual Capacity x x ○ ● ● ○ ○Mix Practical Productive Capacity

x x ● ● ● ● ●

Planning factor x x ○ ○ ● ○Utilization factor x x ○ ○ ○ ○ ○Overall Equipment effectiveness

x x x x x x ● ○ ○ ○ ○ ○ ● ○ ● ● ○ ○ ●

Textile Useful life x x x x x x ● ○ ○ ●Textile Rotation Index x x x x x ● ○ ●Textile among customer x x ● ○ ○HR Productivity x x x x x ○ ○ ● ● ● ○Direct HR Yield x x x x ○ ● ● ● ○ ○Indirect HR Yield x x x ● ● ●Overtime impact x x x x ○ ○ ○ ○ ○ ● ○Electrical Productivity x x x x x ● ○ ○ ○ ○ ● ○ ● ●Gas Productivity x x x x x ● ○ ○ ○ ○ ● ○ ● ●Oil Productivity x x x x x ○ ○ ○ ○ ● ○ ● ●Water Productivity x x x x x ○ ○ ○ ○ ● ○ ● ●Energetic Resource Productivity

x x x x x ● ○ ○ ○ ○ ● ○ ● ●








PHASE 1:


PHASE 2:







Table of Content

• The Context




21







Benchmarking and Dissemination

Benchmark can allow to each Laundry to:

•really understand its performance in the market thanks to a comparison with other laundries regarding on the critical factors (HR, Machinery, Textiles & Utilities) ->Category association.

•easily identify improvement area;

•enhance its excellence area;

•quickly start improvement process on the basis of the priority forthe specific market

Market Segmentation Mix Machinery Utilities




Benchmark

Data Collection Kpi’s Evaluation

•Mandatory data/optional data;•Automated web base tool;•Data entry guided and errorproof;•Data immediatly accessible;

Laundry Sector Report:•Emerging trends•Critical issue of the sector

Repeatquestionnaire

with a predetermined

frequency

•obtain useful informationthat allow to verify theeffectiveness of animprovement for a laundryregarding a specific KPI;•verify the effectiveness ofthe process best practicesharing within the EBLI;•promote project that allowsto moving forward the limitfor laundries processoptimization;•to verify the trends andcritical emerging of thesector effectiveness of theAssociation for their work isreadily identify trends andemerging critical.




Dissemination Plan

•The guidelines describing the measurement and improvement system has been published and presented in a congress promoted by Assosistema.

•University will constitute a centre of expertise and applied research on the laundry sector;

•University and EBLI will define a training program to provide companies all the knowledge which is needed to implement the system and to apply all the proposed techniques;

•University will support the development of specific professionals (graduates) that can support laundries in the performance improvement.








PHASE 1:


PHASE 2:




All these activities aim to improve the industrial culture of the Italian companies of laundry sector by transferring all the knowledge deriving from other industrial sector.




Table of Content

• The Context




26







Conclusions

•Measurement and improvement system of general validity

•possibility for the system to become a standard in the industrial sector

•manage the dissemination phase in order to ensure full implementation of the methods and techniques

•the collaboration with companies associations such as AssoSistema allows University to achieve high level results that can be quickly spread to a large number of companies.

Authors have analyzed different type of laundries, have caught all their peculiarities, have deployed a system which take them into account and finally have experimented the system and have implemented the needed adjustments.

•Many improvements and developments are still possible, and the results of the benchmarking will give the direction to follow.

Measuring and Improving Manufacturing plant performances: Development and Dissemination of a customized Model for the


University of RomeTor VergataDepartment of Mechanical Engineering,Industrial Engineer Research Group Contacts:

Vittorio [email protected]

Alessio [email protected]

Vito [email protected]

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University of Rome Tor Vergata - summerschool-aidi.it