Curriculum Development

of Master’s Degree Program in

Industrial Engineering for Thailand Sustainable Smart Industry

Pisut Koomsap, AIT

Athakorn Kengpol, KMUTNB

Supapan Chaiprapat, PSU

Course 6: Digital Factory

Course Objective

Utilization of digital technology for modeling, and communications to

• configure

• model

• simulate

• assess, and

• operate a manufacturing process

2

Digital Factory

Course Learning Outcomes (CLOs)

Course Learning Outcome (CLOs) BloomLevel PLO

CLO1 Explain the principles of digital factory understand

PLO1,3 (Apply knowledge and method to design an Industry 4.0 system, Utilize big data and real-

time data to support smart systems)

CLO2

Discuss applications of automated

equipment understandPLO2 (Implement smart production and co-

created product)

CLO3 Explain roles of AI in digital factory understand

PLO3,8 (Utilize big data and real-time data to support smart systems, Manage smart production

systems)

CLO4

Create a basic information model of a

production process apply PLO8 (Manage smart production systems)

CLO5

Identify potential risks and gains of the

existing production system, and propose

solutions analyze PLO8 (Manage smart production systems)

CLO6

Function and communicate effectively in a

team skill PLO9 (Communicate effectively)

CLO7 Engage in independent lifelong learning skill PLO11 (Demonstrate self-development)

3

Digital Factory

How this class is conducted: Learning Model

• LOVE model found by Prof. Pisut Koomsap, AIT

4

Teaching & Learning Methods for Module 1

Activity Teaching & Learning Method Lecture/

Workshop/Lab/Self

study

Kolb’s Learning Cycle Learning

Experience

1 Illustration of traditional factories in contrast with digital

factories

(Wk1)

Lecture (30 mins) Concrete Experience Observing

2 Discussion on readiness of industry (infrastructure,

equipment, human resources, etc) (Wk1)

Lecture (30 mins) Reflective Observation Learning

3 Review on factory digitalization (group work) (Wk1) Self study (30 mins) Concrete Experience Learning

4 Class discussion (group presentation)(Wk1) Lecture (30 mins) Reflective Observation Learning

5 Lecture on digital factory (Data Flow Diagram and

contribution of AI in digital factory) (Wk1)

Lecture (60 mins) Abstract

Conceptualization

Observing

6 Factory visit (Assignment: current data flow) (Wk2) Lecture Concrete Experience Visiting

I: Overview of Digital Factory

5

Digital Factory

Activity 1: Illustration of traditional factories in contrast with digital factories

• Traditional Factory

• Digital Factory

• Summarization of Digital Factory

6

Activity 2: Discussion on readiness of industry

Share your ideas. Are we ready for the digital transformation?

https://www.ssim.ac.in/blog/how-to-prepare-for-group-discussion/

Activity 3-4: Review on factory digitalization and discussion

Search for case studies of factory digitalization and share them with the class.

https://www.123rf.com/photo_62742793_stock-vector-big-data-and-data-analysis-information-data-and-gadgets-icon-flowing-through-the-searching-operation.html

https://en.wikipedia.org/wiki/Industrial_Revolution

Activity 5: Theoretical background on Digital Factory

Industrial Revolution

• Began in Great Britain (mid 18th

century)• Hand production methods to

machine• Steam power and water power• Iron production process• Textiles were the dominant industry• Rise of a mechanized factory system

https://www.presentationpoint.com/blog/data-signals-triggers-industry-4-0/

Activity 5: Theoretical background on Digital Factory

Industry 4.0 Drivers:• Data- Rise in data volumes or

“Big Data”• Connectivity- A network of

businesses in the age of economic globalization

• Customers- Expectations are changing quickly

https://www.reliableplant.com/Read/30933/factors-driving-industry

1760s 1840s 1950s Today

https://sentifi.com/blog/industry-4-0-beyond-the-prospects-of-your-job-being-automated-part-2/

Activity 5: Theoretical background on Digital Factory

Industry 4.0 Enablers: ??

https://www2.deloitte.com/insights/us/en/focus/industry-4-0/smart-factory-connected-manufacturing.html

Traditional Factory:• Non-traceable WIP• Inconsistent

product quality• Uncontrollable

waste• Lack of flexibility• Ineffective strategic

planning• Higher production

cost in the long run

Activity 5: Theoretical background on Digital Factory

Traditional VS Digital

Activity 5: Theoretical background on Digital Factory

• Digital factory is the key topic in Industry 4.0. • According to the Association of German Engineers (VDI), digital factory is

o ‘‘a comprehensive network of digital models, methods and tools, including simulation and 3D/virtual reality & visualisation,

owhich are integrated through continuous DATA management’’,

owith the goal to design, model, simulate, evaluate and optimise products, processes and systems before any modification is actually carried out on an existing (or new) physical system.

• Its meaning in Industry 4.0 is extended, implying an entire value network.

Digital Factory Definition

Activity 5: Theoretical background on Digital Factory

Data Flow Diagram (DFD)

A data-flow diagram is a way of representing a flow of a data of a process or a system (usually an information system). The DFD also provides information about the outputs and inputs of each entity and the process itself. A data-flow diagram has no control flow, there are no decision rules and no loops. Specific operations based on the data can be represented by a flowchart. (https://en.wikipedia.org/wiki/Data-flow_diagram)

A data flow diagram is a graphical representation of the “flow” of data through an information system, modelling its process aspects.

Activity 5: Theoretical background on Digital Factory

Data Flow Diagram (DFD)

DFDs show three types of internal system component: external entities, processes, data flows and data stores. (https://www.lucidchart.com/pages/data-flow-diagram)

1. External entity: A system that sends, receives data or communicates with the system being programmed.

2. Process: Any process or action that changes data or produce output.

3. Data store: Files or repositories that hold information for later use.

4. Data flow: Routes or directions that data take between the systems, processes, and data stores.

Data Flow Diagram (DFD): Components

Activity 5: Theoretical background on Digital Factory

https://www.smartdraw.com/data-flow-diagram/

Data Flow Diagram (DFD): Example

https://www.techinasia.com/talk/online-shopping-catching-women-india

Activity 5: Theoretical background on Digital Factory

Data Flow Diagram (DFD): Rules and Tips

• Each process should have at least one input and an output.

• Each data store should have at least one data flow in and one data flow out.

• Data stored in a system must go through a process.

• All processes in a DFD go to another process or a data store.

(https://www.lucidchart.com/pages/data-flow-diagram)

https://blog.commlabindia.com/elearning-design/tips-to-design-effective-elearning

Activity 5: Theoretical background on Digital Factory

Data Flow Diagram (DFD): Challenges after the session

• What kind of data we will normally find in the factory?

• What scale of data that flow within the factory?• How to collect such a great amount of data?• After the data collection, how to analyze them

efficiently? Do the traditional method still be your choice?

Assignment 1: Topic summary

Students are assigned to summarize what they have learned in this topic in a one A-4 page. In this note, aside from the theoretical material, students can give reflection on how this class is handled, as well as suggestions to improve teaching and learning methods.Due date: Next week.

Students to visit a case-study factory. Learn about its processes and data flow. Record critical information for your DFD assignment.

Activity 6: Visiting a factory

Assignment 2: DFD of the factory

Students are assigned to create a data flow diagram of the factory they visited. Focus on • core processes of the factory and data that go through such processes• how the data are conveyed between the processes• how the data are stored for later use.

In case of data leakage, missing, inaccuracy, and etc., what are the factory’s countermeasures?

Due date: One month