Rev 1.0

White Paper“SMKL（Smart Manufacturing Kaizen Level）～Approach to Smart Manufacturing～（first published edition）

2020/4/1

IAF (Industrial Automation Forum)/CLiC (Control Layer Informational Cooperation)/KPI Subcommittee

1Table of Contents
Foreword ............................................................................................................................................ 4

1.

１.1

Background and Challenges ...................................................................................................................4

１.2

Proposals .............................................................................................................................................5

SMKL Overview .................................................................................................................................. 7

2.

2.1

Key Features of SMKL ...........................................................................................................................7

2.2

SMKL Deployment Environment.............................................................................................................8

2.3

Other Indicators ......................................................................................................................................9SMKL Indicator ................................................................................................................................ 10

3.

3.1

Maturity Levels .................................................................................................................................... 10

3.2Management Levels.............................................................................................................................. 12

3.3

About SMKL’s Maturity Data ............................................................................................................... 14

3.4

About SMKL levels name ..................................................................................................................... 14

3.5. SMKL Implementation Procedures .......................................................................................................... 15
4.

How to evaluate the current state of SMKL ......................................................................................... 17

5.

Determination of SMKL improvement targets ...................................................................................... 21
5.1

Use case to make the first target "management level".............................................................................. 21

5.2

Use case to make the first target "KPI" .................................................................................................. 22

6.

Smart Manufacturing Investment Decision .......................................................................................... 23

7.

About SMKL Operating .................................................................................................................... 24
7.1

PDCA Sequence Diagram with SMKL .................................................................................................. 24

7.2

Sequence diagram of KPI management work ......................................................................................... 25

８.

SMKL Technology Map for Smart Manufacturing ............................................................................. 26

９.

Conclusion ....................................................................................................................................... 27

１０.

References .................................................................................................................................... 28＜Appendix A＞「KPI（ISO 22400-2）」 ............................................................................................. 29＜Appendix B＞"SMKL KPI management sheet" ................................................................................... 30＜Appendix C＞「Smart Manufacturing Investment Plan Application」 ................................................. 33＜Appendix D＞”SMKL KPIs Maturity Level Radar Chart ” .................................................................. 352

＜Appendix E＞"SMKL integrated management sheet" .......................................................................... 37＜Appendix F＞"Comparison with other indicators" .............................................................................. 38

3

1. Foreword
１.1

Background and Challenges

We often see or hear a word “Industry 4.0 (I 4.0)” which is a near-future digitalized manufacturing concept
introduced by Germany in 2011. Not only this but also people popularly use the terms “Industrial IoT (IIoT:
Industrial Internet of Things)” and “smart manufacturing (SM: Smart Manufacturing)” in manufacturing area.
On the other hand, although the introduction of Smart Manufacturing is gradually progressing at the manufacturing sites of plants and a lot of laboratories and manufacturing companies conduct many test operations suchas test beds, we can find only a few actual efforts, and a few investment decisions are made by locally assessing
the cost-effectiveness of Smart Manufacturing.
Factory owners and company directives have high expectations that applying Smart Manufacturing into theirfactory will improve their productivity, quality, inventory control, product traceability, efficient maintenance,and environmental conditions. However, It need huge investment when they apply full-system that converts all
the information in a factory into Smart Manufacturing at once and analyse it, and link the information to the
supply chain at once, and it is difficult for decision makers to judge in feasibility study how much they should
promote Smart Manufacturing at first, and when they should continue, enlarge or terminate the trial Smart Manufacturing project because they are hard to forecast and evaluate the project cost-effectiveness well. Especially
SMEs (Small and Middle size Enterprises) manufacturing company has little chance to have consulting about
Smart Manufacturing because they tend to have no internal Smart Manufacturing specialists and they have noconnection to consultants and system integrators (SIers) who are familiar with Smart Manufacturing.
It is tremendously difficult to achieve suitable Smart Manufacturing for size of their manufacturing factoryand for their area of business. For example, there are a lot of things they take into considerations to achieve
product traceability in the management of inventory and product life cycle. How do they introduce equipment
to attach IC tags to their products? Do they need additional equipment or systems to collect data from IC tags?
How do they analyse the information collected throughout system and products? Is it possible to recover investment utilizing these analysed data against the cost of IC tags? In order to achieve this goal, they will spend a lotof time and resources to consult a various kinds of stakeholders including equipment manufacturers machinebuilders and IT integrators by themselves, and Although, even if they achieved product traceability on this way,
it does not mean achieve Smart Manufacturing.
Regarding Smart Manufacturing, several Smart Manufacturing authorities and consortium in Europe, U.S.,
China, Japan, Singapore, and others propound and advocate maturity levels. They are mostly based on the Capability Maturity Model Integration (CMMI: Capability Maturity Model Integration, ISO/IEC 15504) for S/W.
However, it is very difficult to understand and use them because these Smart Manufacturing maturity model
contains organizational management scheme and evaluation for employee education, Therefore, unfortunately,
as of April 2020, there are no international standards for Smart Manufacturing maturity model.

4

１.2

Proposals

To solve these issues, this White Paper proposes the Smart Manufacturing Kaizen Level (SMKL) as a simple
maturity level for Smart Manufacturing based on Key Performance Indicators (KPIs: Key Performance Indicator) for productivity, quality, inventory, maintenance, and environment. This indicator scoops from worker or
installation to supply chain.
SMKL makes it relatively easy for factory owners and manufacturing engineer to conduct feasibility study
for Smart Manufacturing projects. In addition, it is a very simple indicator enough to make people who do nothave expert knowledge in Smart Manufacturing, like plant managers, facility staff consultants, SIers, and evensales staff to discuss about Smart Manufacturing application for the factory.
A purpose of SMKL project is making international recognition and common understanding for this everyone’s simple Smart Manufacturing maturity level not only in Japan but also all over the world. This SMKL is
proposed to ISO/TC 184 as a technical report (TR) of international standards. Regarding on word SMKL, weapplied a term KAIZEN that symbolizes the Japanese method of continuous improvement, because all member
relating to the facility, includes workers and operators, can use this level for improving them like Kaizen activities.
This White Paper defines Smart Manufacturing as "Achieving optimized manufacturing factory based on
clarifying KPIs utilization level calculated through digitalized information in the factory, such as “data collection”, “visualization”, “analysis” and “optimizing” SMKL is defined on 2 dimensional 4x4 matrix which has
2 axis. The vertical axle is 4-level “maturity level” from “data collecting” to “optimizing” and horizontal axle
is 4-level “management level” from” worker or installation” to “supply chain”. Through any Smart Manufacturing project, target facility has current level and goal which are plotted on this index. (See Figure 1).

Level dOptimizing

Level cAnalyzing

Level bVisualizing

Level aCollecting

Maturity
Level
Management
Level

Workeror
Installation
Level 1

Workstation

Factory

Supply Chain

Level 2

Level 3

Level 4

Figure 1 SMKL (Smart Manufacturing Kaizen Level)5This SMKL White Paper consists of following two parts.
Part1 White Paper on Smart Manufacturing Kaizen Level - clarifying Smart Manufacturing level using KPIs
(First Edition) -Implementation into factory This paper target people concerning manufacturing directly. It provides for self-diagnosis and improvement
for Smart Manufacturing levels utilizing SMKL.
Part2 White Paper on Smart Manufacturing Kaizen Level for Sales and Consulting (tentative): (under consideration)
This paper targets suppliers providing for Smart Manufacturing equipment, machine, installation, software,
solutions and consulting services such as equipment manufacturers, machine builders and consultants. This
paper helps to explain how their products and services realize Smart Manufacturing concepts using SMKL.

6

2.

SMKL Overview

SMKL is a simple maturity level indicator defined on 2 dimensional 4x4 matrix which has 2 axes. The verticalaxle is 4-level “maturity level” and horizontal axle is 4-level “management level. This shows how well thefactory has achieved smart manufacturing (Figure 1).

2.1

Key Features of SMKL

1) This maturity level provides for a simple index which shows "What is the purpose of Smart Manufacturing
project (KPI)", "On which area the project targets", and "How much level it does and will achieve "2) SMKL shows “evaluation for each path to reach target Smart Manufacturing maturity level” according to“Installation and worker”, “workshop”, “factory” and “supply chain” units.
3) SMKL helps continuous improvement (Kaizen) activities in Smart Manufacturing, with “understanding
Smart Manufacturing maturity level”, such as “data collecting”, “visualizing”, “Analysing” and “Optimizing”.
4) SMKL has a common understanding of "systematic investment decisions for the introduction of smart
manufacturing in factories" among factory owners, manufacturing engineers, managers, workers, andother stakeholders in the factory.
5) SMKL can be a tool for Smart Manufacturing consultants and Smart Manufacturing SIers to make theircustomer easily understanding future vision and target on their facility with evaluation their factory with
SMKL indicator.

7

2.2

SMKL Deployment Environment

To achieve Smart Manufacturing with SMKL, both managements’ will and direction and employees’
eagerness that they want to realize ideal working condition are needed.
1) The managements direct to promote Smart Manufacturing project in factory.
2) The management gives practical improvement targets such as productivities and quality.
3) The management have common Smart Manufacturing benchmark or criteria throughout
several different factory.
4) The workers want to give up manual input and handwriting logging. They request to
digitalize and automate logging factory management data,
5) Maintenance staff need to determine why production factory stop. Digitalized datacollected by sensors will help the process.
6) Using predictive maintenance with these digitalized data, they optimize production
and maintenance plan.
SMKL is suitable for conversation tools that express the direction of visualization and improvement among
the managements who makes investment decisions for Smart Manufacturing and practitioner who install equipment in the field such as the workers, consultants, SIers, and vendors.
Therefore, it can be a suitable Smart Manufacturing evaluation method for continuously improving by meansof a bottom-up approach taking up executioners’ ideas and suggestion for betterment their working fields, rather
than top-down approach that only managements determine them all.
SMKL aims to improve factory efficiency and to create a comfortable working environment through Smart
Manufacturing. SMKL is not intended to strictly manage and operate factories. When SMKL is used for strictly
management and operation, just raising the level of SMKL becomes its purpose. In this case, if the level of
SMKL is not raised, the investment for the project will not be made even though it is cost-effective. Or somemanagements do not want to use this indicator because it looks “level down” due to changing its viewpoint.
SMKL is just a rough indicator for Smart Manufacturing feasibility study. Therefore, it is used as a conversation tool between the plant manager and the person in charge of the site, and when they make actual decision
for investments, they should prepare for a facility investment plan to measure the cost-effectiveness. (Refer to<Appendix C> " Smart Manufacturing Investment Plan").

8

2.3

Other Indicators

Several governments and initiatives advocate corporate diagnostic indices for Smart Manufacturing. such as
The "DX (Digital Transformation) Promotion Indicators" recommended by the Ministry of Economy, Tradeand Industry of Japan, the "SIRI (Smart Industry Readiness Index) index" prepared by the Government of Singapore with reference to I 4.0 Please refer to the <Appendix F> "Comparison with other indicators" and whichsummarizes the differences between SMKL.
Standing on analogy of health check, the DX and SIRI indicators are "Annually questionnaire and blood test
" diagnostics conducted by doctors and other medical specialists. On the other hand, the SMKL indicator is a“daily weight check” by yourself. Managements and executioners use SMKL not only for short-term PDCA
cycle managements of improving factory considering cost-effectiveness but also for middle and long term (suchas 5 years) Smart Manufacturing application project.
Each indicator has its own characteristics suits for each application. However, it is recommended for SMEs
to apply the SMKL indicator because it is hard to find Smart Manufacturing specialists in their area and SMKL
can provide for an easy-to-understand indicator for all managements and executioner. It is also suitable for small
start.

9

3.

SMKL Indicator

3.1 Maturity Levels
Maturity level consists of 4 levels; level a is electrized “data collection”. level b is “visualizing” using HMI
devices, level c is “analysing” collected data and level d is “optimizing” by Ais and automation systems. (seeTable 1).
At any level, each process shall be digitized automatically or simplified manually.
For example, if manufacturing data is stored in electrical database and it is indicated by printed paper, it
should be level a, not at level b.
In another case, data used for managing manufacturing facility is indicated by HMI device such as monitor
or PC display however it does not analyse them or does not alert practitioners, it should be level b. it does notreach to level c.
Furthermore, when the system can analyse data, however its countermeasure is manually installed to thefacility, it should be level c, not level d.
In order to achieve level d, it is necessary to utilize automatic processing and algorithms utilizing AI, etc. torecognize and execute improvement from the results.
If the facility does not reach to level a, it should be level 0 (zero).

10Maturity Level
Level aCollecting

Table 1 Maturity Level
Evaluation criteria
Image diagram
・ Production data and machine
status is collected and stored inelectrical method, automaticallyor manually with simple action(example: scanner, code reader)

Exemption: electrical copy of
handwriting daily report*This
does not apply to entries in Excel,
such as handwritten daily reports.
Level b・ Charts and lists are automatically generated in real time based
Visualizing on collected data of the level a.

Example・
Automaticallystored in thedata server

・ Automatic
display line
graph of data
・histogram

Exemption: Manually generating
charts and lists using table calculation tools.
Level c・ Charts and lists include realtime analysis data that shows theAnalyzing difference between Level b andtarget values.
·It warns automatically to operators when it is necessary for a variance to be adjusted. In addition,
for any difference which requires
action against the difference, a
notice urging action to the parties
concerned shall be automaticallygiven.
Level d·Automatically perform feedback
control on people, devices, andOptimizing other objects based on Level canalysis results.

・process skip
control・Process failure management·ActionWarning

・AI・ Automatic
adjustment

This basic idea of maturity level can be applied to indicate Smart Manufacturing capability of each hardware,
software, and solution products. For example, sensors which collect data from the facility is “level a” capability,
HMI device which indicate data has “level b” capability, CPU and programs analyzing these data is “level c”
capability and AI system for optimization has “level d” capability.(8.Refer to "Technology to realize Smart
Manufacturing ").

11

3.2 Management Levels
For factory automation plants (FA), Management levels are set to 4 levels, workers or installations is definedas Level 1, workstations as Level 2, the factory as Level 3, and the supply chain as Level 4 (Figure 2, Table
2).
Whether the management level of SMKL is managed accurately or easily depends on how it is used. Whenyou start using SMKL, we recommend that you manage it more easily than accuracy. For example, all workstations in the factory are required to reach level 3, but it is okay if one workstation reaches level 3. It will
increase the motivation of smart manufacturing stakeholders.
In addition, it is necessary to change the definition of the management level if the domain changes. For example, in the field of building automation (BA), level 1 is a room, level 2 is a floor, level 3 is a building, andlevel 4 is outside of the building.
This document introduces an example in a certain Factory Automation plants.

Level 4：Supply Chain
Level 3：Factory
Level 2：Workstation
Level 1：Worker or Installation

12

Customers

Figure 2 SMKL Management Levels

Distributors /Dealers

worker

Logistics

Installation

Product Warehouse

worker

Packing

Parts warehouse

Parts suppliers

Installation

Table 2

Management Level
Level 1
Worker or Installation

SMKL Management levels
Evaluation criteria
Management objective describes the smallest unit of the manufacturing process.
(IEC 62264:2013, Levels2,1,0, Work Units)

Example·human cell·equipment·machine tools·inspection
equipment
・Product processes (Processing, assembly, painting,etc.)·product line
・factory of a
product

Level 2

Management objective consists of one or more workers or InWorkstation stallation and has the basic functions of the manufacturing
process.
(IEC 62264:2013, Levels 3, Work Centers, Area)

Level 3

Management objective consists of one or more workstations
Factory in a location. Series of these workstations perform a manufacturing process.
(IEC 62264:2013, Levels 4, Enterprise, Site)
The supply chain includes the outside of the factory.
・entire distribuSupply Chain (Enhancement Industrial 4.0, Connected World)tion of the product: parts makers, logistics,
and customers.

Level 4

*Supplement:
Level 1: "Worker or Installation" can be called "Unit of Work" or "Worker or Equipment".
Level 2: "workstation" can be called "workplace" or "production line" or "manufacturing process"13

3.3 About SMKL’s Maturity Data
It is desirable to create maturity data by referring to ISO 22400 (<Appendix A> "KPI (ISO 22400-2)") as KPI
in the factory.
There are generally a variety of products, and the required KPIs differ depending on the factory. You need to
select a KPI suitable for your factory from ISO 22400 or create a new KPI. If you want to create a new KPI,
please refer to <Appendix B> "SMKL KPI Management Sheet".
Data collection methods, visualize methods, analysis methods, and optimize methods differ depending on thetype of KPI. Which KPI you choose is also an important decision to invest in smart manufacturing.
This white paper provides examples of key production, inventory, cost, quality, maintenance, and environmental KPIs in electronic component assembly plants.

3.4 About SMKL levels name
The maturity levels described in Section 3.1 and the Management levels described in Section 3.2 are collectively referred to as follows.
"Management level" + "Maturity level"
For example, if the Management level is “2” and the maturity level is “b”, then the name is level "2b".
If the management level is "2" and the maturity level is "0", it is called "2 zero".

143.5. SMKL Implementation Procedures
SMKL is a simple maturity level of smart manufacturing based on KPIs for productivity, quality, inventory,
maintenance, and environment. This indicator scoops from worker or installation to supply chain. The implementation steps are shown in the below (Refer to the operation flow diagram in Fig. 3).
Step 1: First, evaluate the current situation. Manufacturing engineers will consider the KPIs needed for
improvement of Smart Manufacturing. Then use SMKL to assess the management level and maturity level of the current factory.
Step 2: Based on the evaluation results, manufacturing engineers and managers consider the need for improvement. If there is a need for improvement, they will make a smart manufacturing investment
plan that describes all the equipment and factory, data collection methods, cost-effectiveness, etc.
to realize it. (Reference: <Appendix C> " Smart Manufacturing Investment Plan")
Step 3: Submit the investment plan for smart manufacturing to the management when implementing improvement activities. This investment plan can be submitted to management at various times. For
example, 1) factory equipment renewal, 2) factory equipment expansion, 3) company annual
planning, 4) worker improvement activity planning, etc. The owner makes a judgment based on
the SMKL value and cost-effectiveness described in the investment plan, referring to the opinionsof other SMKL-related actors as to whether the investment direction is suitable for the company.
Step 4: If the investment is approved at the owner's discretion, the manufacturing engineer will installequipment such as smart manufacturing and assess whether improvements have been achieved
as targeted. In addition, decide whether to continuously improve the equipment. If the improvement does not reach the target, it is sometimes important to decide to stop investing in smart
manufacturing.
If you want to comprehensively judge various KPIs that are important to your factory, use <Appendix D>"SMKL radar chart by management item" or <Appendix E> "SMKL comprehensive management sheet".
SMKL's ideal is to have the highest 4d level for all KPIs, but that shouldn't be the goal. We will use SMKL
to discuss what we want to do with smart manufacturing between owner and other related actors. It is mostimportant to achieve step-by-step optimal smart manufacturing that is cost effective for your factory.

15

StartContinue according
to Kaizen grow path

Decision on KPIs & Decision on
Management level

Step1

Current implementation Maturity
level evaluation

Need improvement?

No

Yes
Draft implementation investment
planning sheet

Step2

Decision on Target implementation
maturity level
No
ROI Judge

Step3

Go
Adoption and evaluation on selected implementation
Yes
Is it a valuable for further investment?

NoEnd
figure 3

16

SMKL process workflow

Step4

4.

How to evaluate the current state of SMKL

There are two approaches to the evaluation method of SMKL, one is to decide the management target
and the other is to decide KPIs.
1) Evaluation method of first determine the "management level"
You can roughly evaluate the status of smart manufacturing by people, installations, workstations, factories, and so on. The feature of this method is that it does not take much time to evaluate, so even a
manufacturing engineer can easily evaluate it.
This method gives rough idea of smart manufacturing. It is also an effective way to choose a location
for smart manufacturing, or to first use SMKL to get a rough idea of the maturity level of a factory.

2) Evaluation method of first determine the "KPIs"
This method is a general SMKL usage and follows the SMKL workflow in Figure 3. It is used when the
KPI that you want to manage is decided in advance, such as the equipment operation status and power
consumption. It has the advantage that the purpose of improvement is easy to set.
However, for evaluation, not only manufacturing engineers but also members who have experience ininstallation and factory management should be included.

17

4.1

Evaluation method use case to select "Management level" firstFirst, select some candidates for management targets that you want to make smart manufacturing.
Next, the manufacturing engineers and managers related to the target will judge how far smart manufacturing
is currently done, along with the reasons, referring to SMKL in Table 1.
As a point at this time, please select the KPI that seems to have the highest SMKL level (operation information,
power consumption, temperature control, etc.) (see Table 3).
Table 3 Use case of evaluation method that first determines "management level"
No.
ManageMaturity
Reasonment Level
level
1 Factory Aa
The operation record information of the entire factory is collected and accumulated as electronic data, but the graph of theoperation record is printed and posted on the bulletin board.
2 Factory Bb
The power consumption of the entire factory is visualized, andthe actual data is also displayed as a graph on the monitor. However, there is no function to set a threshold value and issue an
alarm, and a person analyzes and judges by looking at a graph.
3 Factory CdAir conditioning is automatically managed throughout the factory. A temperature sensor and humidity sensor are attached to
the required positions in the factory, and the correction control is
automatically performed at 25 ° C ± 1 ° C.
4 Factory D
zero
The entire factory is mostly manual, and there is no digitized
KPI data.

You can use the SMKL index to compare and evaluate the smart manufacturing status of each factory, as in
the use cases in Table 3.
The maturity level of each KPI is basically considered with reference to the maturity level in Table 1.

18

4.2

Evaluation method use case to select "KPI" firstFirst, select the KPIs you need for your factory.
It is desirable to create maturity data by referring to ISO 22400 (<Appendix A> "KPI (ISO 22400-2)") as
KPI in the factory.
There are generally a variety of products, and the required KPIs differ depending on the factory. You needto select a KPI suitable for your factory from ISO 22400 or create a new KPI. If you want to create a new KPI,
please refer to <Appendix B> "SMKL KPI Management Sheet".
This white paper provides examples of key production, inventory, cost, quality, maintenance, and environmental KPIs in electronic component assembly plants (see Table 8).
Data collection methods, visualize methods, analysis methods, and optimize methods differ depending on
the type of KPI. Which KPI you choose is also an important decision to invest in smart manufacturing (See theselection reason column in Table 8).
Next, select the management targets (level) to which you want to apply the KPI.
As a guideline for management targets (level), it is a good idea to choose a place where products with alarge improvement effect are manufactured. For example, products for important customers and mass production.
Then evaluate the SMKL for each KPI.

19

Table 4 Examples of Electrical Parts Assembly Plants
Classification of KPI
KPIs
motivation for selection
proFunction to manage the condition of (1) Installation I would like to analyse which lines and production equipment required for production
operation
cesses are often stopped due to occasional
management stoppages, etc.
Inven- Function to manage the state of(2) Product man- I want to analyse product management andtorywork in process required for proagement
improve the status of work in process.
ductionDeliv- A function to create a production(3) Daily produc- We would like to obtain on-site production
eryplan, considering delivery dates,tion control control information in order to provide acproduct features, equipment recurate delivery date answers to customers. I
strictions, etc.
also want to plan resources.
(4) Hourly pro- I want to change manufacturing instructions
duction con- in real time so that it can be linked with retrol
source reallocation and delivery time according to the difference between the planand the actual result.
Cost
A function to manage worker ID in- (5) Worker per- I want to improve the work cost by looking
formation (work qualification,formance
at the actual results of which product tookhourly wage, authorization history,
management how much man-hours.
etc.) and work status (workload,(6) Worker state I want to improve and analyse work effiwork time, work history, etc.).
management ciency to see if each worker is doing a job
This information is also used for rethat suits their skills.
source allocation and optimal work
allocation.
Quality A function that analyzes measure- (7) Product qual- I want to know whether the product quality
ment data collected from the manuity manage- is stable from the characteristics of productfacturing site and manages andmentinspection.
tracks the quality of appropriate(8) Process qual- I want to catch changes in manufacturing
products and processes.
ity control
conditions (temperature, etc.) and prevent(This information links causes,
product defects.
symptoms, countermeasures and(9) Product trace I want to give an ID to a semi-finished prodconsequences.)management uct in production or a final product to findout from which lot the defect occurred.
Mainte A function to manage master infor- (10) Tool manage- I want to see when to replace jigs and tools.
nance mation (ID, name, etc.) of jigs andmenttools required for production. And a (11) Regular
I want to visualize the maintenance time offunction to manage the schedulemaintenance equipment.
and results of regular maintenancemanagement
and preventive maintenance of(12) Preventive
I want to perform preventive maintenanceequipment.
maintenance before the equipment stops.
management
Envi- A function to manage the target and (13) Temperature I want to eliminate defective products due toronperformance of equipment, air conmanagement environmental changes.
ment ditioning, temperature and humidity (14) Humidity
I want to eliminate defective products due toof buildings and electric energy.
management environmental changes.
(15) Power con- I want to reduce the power cost by suppresssumption
ing the peak power by linking with the promanagement duction plan.

20

5.

Determination of SMKL improvement targets

Next, we determine the improvement target based on the current value of SMKL. This white paper presents
two cases.

5.1

Use case to make the first target "management level"

This method gives rough idea of smart manufacturing. It is also an effective way to choose a location for
smart manufacturing, or to first use SMKL to get a rough idea of the maturity level of a factory.
For example, consider the following based on the current evaluation results by SMKL.
1) Factory A: Is it necessary to stop printing out KPI data and display it on the monitor in real time? (fromSMKL level a to level b)2) Factory B: Is it necessary to analyse the power consumption of the factory and issue an alarm? (SMKL
level b to level c). Or is it not necessary to visualize the operating status like Factory A?
3) Factory C: Air conditioning is level d, but is it necessary to visualize the power consumption like FactoryB?
4) Factory D: Is it necessary to promote smart manufacturing?
Manufacturing engineers and owners who make investment decisions will be able to discuss improvement
goals from the same perspective of SMKL.

However, as the maturity level is raised and the management level is expanded, investment costs will also
increase, so it is necessary to consider cost effectiveness and implement possible improvement items within thebudget.

21

5.2

Use case to make the first target "KPI"

This method is a general SMKL usage and follows the SMKL workflow in Figure 3.
It is used when the KPI that you want to manage is decided in advance, such as the equipment operation
status and power consumption. It has the advantage that the purpose of improvement is easy to set.
However, if you choose a lot of KPIs, the investment cost will increase accordingly. You need to consider
cost-effectiveness and implement the best improvements you can make within your budget. If your budget is
exceeded, it is also important to plan a step-by-step long-term level-up in separate years.
It is also important to judge that KPIs that are ineffective for your company will not be improved.

22

6.

Smart Manufacturing Investment Decision

In many cases, choose KPIs, maturity levels, and management levels that can have a significant return on
investment in improving your factory. At first, it's a good idea to choose something that is easy to get started
and effective, including education for smart manufacturing (see Table 24).
And, it is best for many people, such as manufacturing engineers, managers, and owners, to understand the
SMKL index before starting smart manufacturing.
Based on the evaluation results, manufacturing engineers and managers consider the need for improvement.
If there is a need for improvement, they will make a smart manufacturing investment plan that describes all theequipment and factory, data collection methods, cost-effectiveness, etc. to realize it. (Reference: <Appendix C>" Smart Manufacturing Investment Plan").
Manufacturing engineers create smart manufacturing investment plans with the following (Reference: <Appendix C> " Smart Manufacturing Investment Plan"):a) Management locationb) SMKL levels before and after achievementc) Selected KPId) Easy-to-understand explanation of the contents before and after improvemente) Investment costf) Investment effect (reduction time, improvement cost, side effects, other precautions)
Even if SMKL has not leveled up within the 4x4 square, you should invest if the direction of improvement
and the effect of sufficient improvement are expected. Also, even if you do not expect a significant cost effect,
you should invest if there are other secondary or long-term effects. For example, training new employees regarding smart manufacturing and increasing worker motivation.
Table 5

Examples of SMKL Status and Improvement Targets

KPIs(P)production(I)stock(D)delivery date(C)Cost(Q)Quality(M)maintenance(E)Environment(1) facility operation management(2) physical control(3) daily production control(4) production control by time(5) Worker Performance Manage(6) operator status control(7) product quality control(8) process quality control(9) product tracking management(10) tool management(11) routine maintenance manage(12) preventive maintenance man(13) temperature control(14) humidity control(15) power management

Current Level (Before)

Target Level (After)

3b
1b
2a
0
0
0
0
0
0
0
0
0
1a
0
0

3b
2b
2a
1a
0
0
0
0
0
2a
0
0
1a
0
1b

23

7. About SMKL Operating
For improvement activities by SMKL, it is necessary to clarify the roles of managers and otherpersons in charge of each role in the factory.

7.1

PDCA Sequence Diagram with SMKL
Extract the actors required to use SMKL and create a UML (ISO / IEC 19501: 2005) sequence
diagram with PDCA (see Figure 4).
PDCA: Plan: Planning, Do: Execution, Check: Confirmation, Act: Next Action.

Owner

Manager

Manufacturer

EngineerSet Maker

KAIZEN instruct

SMKL Started

KPI review

Data selection

Data collection

SIer
Data collection

Check

Make an investment plan

instruction

Execute an investment plan

Plan

GO
Make installation
Make installation
Introduction

Do

Operation
Check the result

Judge
Continued
investment

Improvement completed

Done

Next Action

Figure 4

24

Check

Operation confirmation

PCDA Sequence Diagram with SMKL (Example)

Act

7.2

Sequence diagram of KPI management work
Create daily, weekly, and monthly actor workflows for the KPI items in Table 8 (see Figure 5).

Operator

LeaderChief

Manager

Status Input

Monitoring

ReportCheck

NG
KAIZEN Action

Director

Owner

NG

Daily

Instructions
Cause analysis & improvement plan (change resource plan, etc.)

Check

ReportCheckNG

WeeklyCause analysis & improvement plan (change resource plan, etc.)

Check

ReportCheckNG

KPI Review

Figure 5

Monthly

Cause analysis & improvement plan (change resource plan, etc.)

Business flow for production (P) and facility operation management (1) in Table 24 (example)

25

８. SMKL Technology Map for Smart Manufacturing
When a vender provides customers with products and solutions related to smart manufacturing, the
SMKL indicator can be used to clearly explain what level of product is useful (see Figure 6). In addition, customers can quickly realize the optimum level of smart manufacturing in factories by using
the products and solutions.
·At the data collection level, various sensors, networks, and 5G products suitable for KPI·At the visualization level, visualization products or applications such as HMI displays or SCADA·At the analyzing level, edge computing·At the Optimizing level, system solutions that utilize various AI, etc.
·it is necessary to consider security and utilize the cloud in order to upgrade the coverage from thefactory to the supply chain.
Vender will be able to effectively sell their equipment, facility, software, solutions, etc. by using
SMKL to introduce the best products related to smart manufacturing in the customer's factory.
Consultants and SIers can use SMKL to explain to customers the services and solutions they offer
regarding smart manufacturing.
Details of this matter are planned in the "SMKL White Paper for Vender (tentative name)".

Level dAI

Optimizing

Cloud,

Edge computing

Level cLevel bServices

Analyzing
Controller, HMI, Solutions,
IT tools, Engineering tools…

Visualizing

Security,

Level aCollecting

Matulity
Level
Management
Level

Workeror
Installation
Level1Figure 626

Eco solutions

Sensors, Networks, 5G

Workstation

Factory

Supply Chain

Level2

Level3

Level4SMKL Technical Map (Example)

９. Conclusion
In this document, we explained SMKL, which is a simple indicator for Smart Manufacturing.
SMKL allows factory owners and manufacturing engineers to have the same level of conversation about
Smart Manufacturing's cost-effectiveness and direction of improvement. SMKL is a suitable tool for PDCA
improvement activities step by step to realize smart manufacturing.
Since this SMKL indicator is simple and easy to understand, it can be used by anyone who understands thebasic concepts of Maturity-Level and Management-level without special expertise or education regarding
Smart Manufacturing.
And, many people regarding smart manufacturing, such as product developers, consultants, SIers, sales,finance and insurance, may be able to use SMKL's technical maps in their businesses.

The IAF / CLiC / KPI Subcommittee will continue to consider these possibilities in the future.
If you are interested in this project, please join the IAF.

27

１０.

References[1] ISA -95 (ISO/IEC 62264): Enterprise-Control System Integration[2] ISO 22400: Automation systems and integration - key performance indicators for manufacturing operations management - Automation systems and integration – Key performance indicators (KPIs) for manufacturing operations management —)[3] X. SHE, T. BABA, D. OSAGAWA, M. FUJISHIMA and T. ITO, "Maturity Assessment: A case study
toward Sustainable Smart Manufacturing Implementation," 2019 International Conference on Smart
Manufacturing, Industrial & Logistics Engineering & 2019 International Symposium on Semiconductor
Manufacturing Intelligence (SMILE & ISMI 2019), Hangzhou, China, 2019, pp. 67-70."Best Faculty Paper Nomination"[4] X. SHE, T. BABA, D. OSAGAWA, M. FUJISHIMA and T. ITO, "A Maturity Model for Sustain-able
System Implementation in the Era of Smart Manufacturing," 2019 24th IEEE International Conference on
Emerging Technologies and Factory Automation (ETFA), Zaragoza, Spain, 2019, pp. 1649-1652.
[5] IAF CLiC (Control layer information coordination opinion exchange meeting), “SMKL Indicators toPromote IoT/Visualization at Manufacturing Sites”, IIFES November 2019,http://www.mstc.or.jp/iaf/event/iifes2019s/SMKL_seminor.pdf, [Accessed: 03-April -20201][6] DX Promotion Indicators, METI, https://www.meti.go.jp/policy/it_policy/dx/dx_seisaku/dx_index/dx_index.html, [Accessed: 03-April -20201][7] SIRI Index, Economic Development Board of Singapore,https://www.edb.gov.sg/en/news-and-events/news/advanced-manufacturing-release.html, [Accessed: 03April -20201][8] IIFES 2019 SMKL Seminar Website in Japanese,http://www.mstc.or.jp/iaf/event/iifes2019s/SMKL_seminor.pdf, [Accessed: 03-April -20201[9] IAF forum 2019 Website in Japanese, http://www.mstc.or.jp/iaf/event/2019f/04chino.pdf, [Accessed: 03April -20201[10] K. Kumagai, M. Fujishima, H. Yoneda, S. Chino, S. Ueda, A. Ito, T. Ono, H. Yoshida, H. Machida,"KPI Element Information Model (KEI Model) for ISO 22400 using OPC UA, FDT, PLCopen and AutomationML", SICE Annual Conference 2017 pp 602 -604
[11] N. Sugawara, S. Chino, A. Ito, T. Ono, H. Yoshida, M. Okuda, Use Case Analysis Integrating OPC UA,
FDT, PLCopen and AutomationML for Factory Automation Systems, SICE 2018 Annual Conference, pp594 -596*SMKL (Smart Manufacturing Kaizen Level) is a registered trademark of Mitsubishi Electric Corporation.
Group names and technical names in this document are trademarks or registered trademarks of their respective companies or organizations.

28

＜Appendix A＞「KPI（ISO 22400-2）」

It is recommended to convert each KPI of ISO22400 to the language of each country.
Classification

productivity index(Efficiency indicators)

Item (English)

Item (Japanese)

Worker efficiency

労働生産性
負荷度
生産量
負荷効率
利用効率
設備総合効率
正味設備効率
設備有効性
工程効率
品質率；良品率
段取率
設備保全利用率
直行率
廃棄度合
廃棄率
工程利用率
手直率
減衰率
機械能力指数： Cm
クリティカル機械能力指数：
Cmk
工程能力指数： Cp
クリティカル工程能力指数：
Cpk
材料使用率
有害物質
危険物質廃棄率

Allocation degree
Throughput
Allocation efficiency
Utilization Efficiency
OEE Index
NEE Index
Availability
Effectivenessquality in- Quality ratio
dicatorPreparation degree(Quality indicators)

Technical usage level
First pass yield
Scrap degree
Scrap ratio
Production process ratio
Rework ratio
Fall-off ratio

Ability index(Capacity index)

Machine capability index
Critical machine capability index
Process Capability Index
Critical process capability index

Environmental indicators(Environmental
indicators)
Inventory management indicators

Ratio of used material
Harmful substances
Hazardous waste ratio
Comprehensive energy consumption
Inventory turns
Finished goods ratio
Integrated goods ratio
Production lost ratio
Storage and transportation lost ratio
Another lost ratio

Conservation index (Maintenance indicators)

Equipment load rate
Mean time between failures
Corrective maintenance ratio

総合エネルギー消費量
在庫回転率
良品率
総合良品率
製品廃棄率
在庫輸送廃棄率
その他廃棄率
設備負荷率
平均故障間隔
改良保全率29

＜Appendix B＞"SMKL KPI management sheet""SMKL KPI management sheet"
Management level:[B Factory ] □level 1, □level 2, ■level 3, □Level4
KPI
Concept (criterion)Ma-

judgment
columnturityLevelselectric (al)power consumption

a

b

c

d

Reason for determining the maturity level

Smart Manufacturing Kaizen Level
Level d:Optimizing
Level c:Analyzing
Level b:Visualizing
Level a:Collecting
InstallationorWorkerWorkstation

Factory*SMKL = Level 0 is all “-”, current level is ”●”, improvement target level is "◎"30

Supply Chain

"SMKL KPI management sheet" (Example 1)
Management level:[B Factory ] □level 1, □level 2, ■level 3, □Level4
KPI
Concept (criterion)Ma-

judgment
columnturityLevelselectric (al)power consumptiona

Are electric power generated electronically?

●b

Are actual values of electric power consumption and unit
energy consumption visualized? (Or is the target value ofthe electric energy and the basic unit digitized, and is thedifference between the electric energy and the actual
value of the basic unit visualized?)●cIs there a function to notify relevant parties (Workers,
manufacturing staff, production engineering staff, etc.)
when there is a difference between the target value andthe actual value of electric energy consumption andbasic unit?(Or is there a function that can analyse thecause of the difference between the target value ofelectric energy consumption and the basic unit and theactual result?)◎dIs there a function of action (Control of facilities andlighting) according to the difference between the target
value and the actual result of the electric energy consumption and the basic unit?

―

Reason for determining the maturity level

The power consumption of the entire B factory is visualized, and the actual data is displayed graphically on the monitor. Tan Therefore, there is no function of setting a threshold value and issuing an
alarm, and a person analyses the graph and makes a judgment. In addition, power consumption is
not visualized for each facility, line, process, or unit.

Smart Manufacturing Kaizen Level
Level d:Optimizing
Level c:Analyzing
Level b:Visualizing
Level a:Collecting

―

―

―

―

―

―

◎

―

―

―

―

―

―

●
●

InstallationorWorkerWorkstation

Factory

Supply Chain―*SMKL = Level 0 is all “-”, current level is ”●”, improvement target level is "◎"31

"SMKL management sheet" (Example 2)
Management level:[B Factory ] □level 1, □level 2, ■level 3, □Level4
KPI
Concept (criterion)Ma-

judgment
columnturityLevelselectric (al)power consumption

a
b

c

d

Are operating results (Operation time, stop time, numberof good products, error code, cycle time, setup time, etc.)
digitized?
Are operating results visualized? (Or is the difference between the target value and the actual value visualized? Or
are various control charts of operating results generated/trended? )Is there a function that can analyse the factors that cause
the difference between the target and actual utilization values?
(Or is there a function to determine silent abnormalities in
the operation results? Example: It detects not only equipment stoppage but also productivity degradation due to efficiency degradation.)●●◎Is there a function to automatically instruct the improvement action based on the factor of the difference between
the operation result target value and the actual value?
(Or is there a function to detect an abnormality in the operation results, stop the equipment, change the manufacturing conditions of the equipment, or support the decision
making to correct or improve the work of the operator?)―

Reason for determining the maturity level

The operation status of the C line is digitized and displayed on the display. When there is a difference between the target value and the actual value, an alarm is notified to the smart phone of the line
reader based on the set threshold. However, there is no instruction to improve the utilization rate byautomatically relocating resources using AI, etc.

Smart Manufacturing Kaizen Level
Level d:Optimizing
Level c:Analyzing
Level b:Visualizing
Level a:Collecting

―

◎

―

―

―

●
●
●

―

―

―

―

―

―

Workstation

Factory

Supply Chain――
InstallationorWorker*SMKL = Level 0 is all “-”, current level is ”●”, improvement target level is "◎"32

＜Appendix C＞「Smart Manufacturing Investment Plan Application」"Smart Manufacturing (SM) Investment Plan"
SMKL※
d
c
b
a

Department
Subject

Date

/ /

KPI

－
－
◎
●
2

－
－
－
－
3

ManagedProduction, Quality, Preventive maintenance, Environment, etc.
After (To-Be)

Before (As-Is)<<Issues>>

－
－
－
－
1

<<improvement point>>

im<<investment cost>>
provement effect<<investment effect>>*SMKL = Level 0 is all “-”, current level is ”●”, improvement target level is "◎"Authorizer

Check

Applicant

33

－
－
－
－
4

"Smart Manufacturing (SM) Investment Plan" (example)
SMKL※
d
c
b
a

Department
Subject

Manufacturing Department A

Date

2019/10/01

－
－
－
－
1

－
－
◎
●
2

－
－
－
－
3

－
－
－
－
4

ManagedWorkstation B
Production, Quality, Preventive maintenance, Environment, etc.

C Streamline drawing checks by introduc- KPI
ing a tablet for workers during product production
Before (As-Is)
After (To-Be)
The worker carried out the product check by the paper
When producing product C on workstation B, workers
drawing in the production of product C in the workcan perform product check on electronic drawings withstation B.
out paper by using a tablet for workers.

<<Issues>>·The data from the old drawings are only available on
paper.
·The new drawings have CAD data and are digitized,
but they cannot be read by a tablet sold directly.
improvement effect<<improvement point>>·All previous drawings underwent high-resolution scanning.
·The data conversion S/W was introduced so that the
new drawing can be displayed directly on the commercial tablet from CAD.

<<investment cost>>
10 tablets (10 thousand yen), 1000 scans (200 yen), 10 CAD data conversion S/W (30,000 yen)
SI outsourcing cost 1 man/month x ¥100 million
Total: ¥250 million<<investment effect>>Time saved: Search time 10 people x 4 products/day x ▲ 0.25 h/case = ▲ 10 h/day= ▲ 2500h/year (250 days)
Improvement cost: - 2500 h x 4 1000 yen (hourly rate) = -10 million yen/year-> Side benefits of investment that can be recovered in 3 months: Workers can magnify drawings ontablets, making them easier to see than paper drawings and reducing errors.

*SMKL = Level 0 is all “-”, current level is ”●”, improvement target level is "◎"34

Authorizer

Check

Applicant2018/10/4
OwnerC

2018/10/2
ManagerB

2018/10/1
EngineerA＜Appendix D＞”SMKL KPIs Maturity Level Radar Chart ””SMKL KPIs Maturity Level Radar Chart ”
Worker efficiency
Corrective maintenance ratio

Level dMean time between failures

Allocation efficiency
OEE Index

Level aFinished
goods ratio

Quality ratio

First pass yield
Inventory turns

Comprehensive energy
consumption

Machine capability index
Process capability index

Ratio of used material

35

”SMKL KPIs Maturity Level Radar Chart ”（example）

Worker efficiency
Corrective maintenance ratio

Level dAllocation efficiency

Mean time between failuresOEE Index
Level aFinished
goods ratio

To-beQuality ratio

As-is
KaizenFirst pass yield

Inventory turns

Comprehensive energy
consumption
Ratio of used material

36

Machine capability index
Process capability index

＜Appendix E＞"SMKL integrated management sheet""SMKL integrated management sheet" (example of use case)*Enter the name of the object to be managed: "-" is left blank.
List maturity levels: Level 0 is all “- ”, current level is“ ● ”, improvement target level is "(◎)"

Maturity LevelNo

KPI(1) OEE(2) Inventory turns

I: Inventory

P: Production

Classification

Management
Level

Management name

４

－

－

－

－

－

－

－

SupplyChine H

３

－

－

－

－

－

FactoryF

Factory
G

－

２

－

－

－

Workstation
D

Workstation
E

－

－

－

１

Installation
A

Installation
B

Worker
C

－

－

－

－

－

1

a

●

◎

－

●

●

●

●

－

2

b

●

－

－

●

◎

●

◎

－

3

c

◎

－

－

◎

－

◎

－

－

4

d

－

－

－

－

－

－

－

－

5

a

●

◎

－

●

●

●

●

◎

6

b

●

－

－

●

◎

●

◎

－

7

c

◎

－

－

◎

－

◎

－

－

8

d

－

－

－

－

－

－

－

－

…

37

＜Appendix F＞"Comparison with other indicators"

There are several indicators of maturity for smart manufacturing like SMKL, and there are differences in how
they are used. SMKL is very simple and easy to use and can be used by various actors. It is suitable for activities
that improve smart manufacturing step by step using the PDCA cycle.
The following is a comparison table of "DX promotion index" recommended by METI, "SIRI index" recommended by Singapore, and "SMKL index".
Items

DX Promotion Index(Ministry of Economy, Tradeand Industry of Japan)

SIRI index (Singapore)

SMKL index

Diagnostic
purpose(Target)Visualization of the state of
DX in enterprises (Corporate
units such as personnel, systems, and IT systems)

Helping companies strengthen their organizational knowledge of I 4.0(3 Components = Process, Technology, Organization)

Visualization of plant information (computerization)(Production, quality, cost,
maintenance, environment,
etc.)

Audience

Executive, Business, DX, IT(Other: Consulting)Management, IT, internal employees,
and external partners and customers

Executives, Facilities, (Other:
IT, Product Development,
Product Sales, Consulting),
Customers

Targetcompany

For all companies(However, it is mainly medium
and large enterprises that havethe ability to promote DX,
such as the establishment of areal DX division.)

From SMEs to multinational enterprises, including discrete and process
manufacturing facilities

For all companies(Large enterprises to small andmedium enterprises)

frequency ofuse(continuity)

Assuming annual diagnosis(Increase or decrease of thenumber of times depending on
the load)
Yes)Continuous use, not one-time evaluation

Used for improvement andproposal activities every time
(It can also be used for new installations and mid-termplans.)

Person who
performed the
diagnosis

Management and employees(IT should not be left alone.)
Currently, web diagnosis isavailable from the Ministry of
Economy, Trade and Industry
website.

No provisions. (Supported by TUVSUD) include cross-functional teams
that include key stakeholders such as
the general manager of the plant andsenior leaders of the operating, digital,
and facilities teams

Same as the intended audience

usage scene

Board of Directors and othermanagement meetings

The company needs to define thescope of the evaluation and choose
whether to evaluate the entire manufacturing facility or individual productgroups(Other: Product development,
product sales, consulting) during improvement activities orthe introduction of new equipment

original
authorUniversity professors, businessexecutives, and group executives

Business owners, technology providers, trade associations, higher education institutions, research institutions,
government agencies, etc.

Manufacturing Engineer andmanager

Achievements
appliedOver 100 companies since
2019
Perform PoC->Data collected is not disclosed.

More than 200 companies have participated since 2018. (33% of SMEs, 12
manufacturers, 14 countries)

Implemented from 2015 at
multiple plants of one company->Open, Several Companies
Planning PoC

Summary

The DX index is like the"Questionnaire and blood testlevels" and is assessed once ayear. It is used as an index
when management consultswith advisors and others tomake management decisions.

SIRI indicator provides a snapshot of
the current state of the enterprise, notfuture possibilities (That is, the sameas the DX index)(Eight Pillars: Operations, Supply
Chain, Product Lifecycle, Automation,
Connectivity, Intelligence, Readiness
Assessment, Structure and Management)

The SMKL index is like a“Body Weight Meter” and isused as an index for continuous improvement activities by
PDCA under self-management, and managers and facility staff examine the evaluation and cost-effectiveness stepby step.

38

White Paper
SMKL（Smart Manufacturing Kaizen Level）～Approach to Smart Manufacturing～（first published edition）
Publication date: April 1, 2020
Publisher: Industrial Automation Forum (IAF)
Control layer information coordination opinion exchange meeting (CLiC) KPI subcommittee

Writer: Mitsushiro Fujishima (Mitsubishi Electric Corporation), chief of the KPI Subcommittee
Supervisor: ITO Akio (FDT Group),
Nobuo UEDA (Tachibana Eletech),Toshio ONO (Japan OPC Council),
Makoto Okuda (PLCopen Japan),
KITAYAMA Takeshi (Mitsubishi Electric Corporation),
Kenji KUMAGAI (Murata Machinery),
TAKEUCHI Tetsuo (FDT Group),
Shinichiro Chino (Mitsubishi Electric Corporation),Takashi Matsukuma (PLCopen Japan),
Takashi YOSHIZAWA (software products),
Hiroshi Yoshida (Omron Corporation),
Naoto YONEDA (Dassault Systems)

IAF Secretariat: Kazunori Fukazawa (In the Manufacturing Science and Technology Center)
Contact: 4th floor, Shinbashi Planning Building 3 -4 -10, Shinbashi, Minato-ku, Tokyo 1050004
E-mail: jim-iaf @mstc.or.jp
TEL:03-3500-4891
URL:http://www.mstc.or.jp/iaf/*Copying, duplicating (Copy) or quoting the contents of this book without permission
is an infringement of the rights of authors and publishers, except in certain cases. If
you have any questions, please contact the IAF Secretariat.

39