Position Paper: Low-cost Prototyping and Solution Development for

Pandemics and Emergencies using Industry 4.0

Srihari Yamanoor

, Narasimha Sai Yamanoor

and Satyakanth Thyagaraja

DeignAbly, San Jose, CA, U.S.A.

DesignAbly, Kenmore, NY, U.S.A.

Self, San Leandro, CA, U.S.A.

Keywords: Artificial Intelligence, Industrial Internet of Things, Rapid Prototyping, Additive Manufacturing, Low-cost

Interventions, Coronavirus, COVID-19, Frugal Engineering.

Abstract: Pandemics, such as the coronavirus pandemic and other large-scale public emergencies, including floods,

volcanic explosions, and earthquakes, require strategic responses for smooth function and restart of industry.

Creative, robust, low-cost, scalable solutions must be deployed for underserved and socially disadvantaged

communities. This effort requires compressing product and process development from requirements

engineering to final testing and deployment, service, and repair, in terms of timeframes, budgets, and related

resource constraints. Exceptional circumstances, such as the coronavirus pandemic, add additional pressures

such as social-distancing requirements. Several development techniques and tools are available for teams to

respond rapidly and effectively to evolving needs in a cost and resource-efficient manner. Industry 4.0

principles can be extended to support frugal development, manufacturing, and operations in diverse

communities. Efforts such as the Maker Movement and the availability of licensing techniques for open

hardware and software development further add to the abilities of teams to enable virtual collaboration,

solution development, customization, and deployment. The paper describes two positions, one that Industry

4.0 can aid in frugal solution development for underserved communities, and two that Industry 4.0 can be

implemented frugally to aid production and quality among underserved and vulnerable communities.

1 INTRODUCTION

The novel coronavirus, SARS-CoV-2, causes the

disease labelled COVID-19 (“Naming the

coronavirus,” n.d.). On Mar 11, 2020, reviewing a

record of over 118,000 cases in over 110 countries at

that point in time, the World Health Organization

(WHO) declared COVID-19 a pandemic (Ducharme,

2020), (Spinelli and Pellino, 2020). Since then, the

pandemic has continued into the second half of 2020,

with uneven recovery and control, globally. The

unavailability of effective treatments or vaccines as

of Jun 30, 2020, has led to varying predictions of

continued infection rates and multiple waves of the

disease globally (Coronavirus Treatment

Acceleration, 2020). Vaccines and therapies

developed to combat the coronavirus will require

manufacturing scaling for quick, wide distribution.

https://orcid.org/0000-0001-9203-6032

https://orcid.org/0000-0003-2241-7176

https://orcid.org/0000-0002-6790-929X

Workplaces, schools, retail establishments, and

several other places where large groups of humans

tend to interact will require special measures

including social distancing, screening for symptoms,

and other preventive as well as control measures

(Kaplan, Hoffman, and Parsons, 2020), (COVID-19

Control and Prevention, 2020).

Besides the COVID-19 pandemic, other

emergencies require interventions such as food and

medication provision through drones or similar

transportation, radiation level measurements, water,

and air quality testing in a rapid, efficient manner.

Such emergencies include floods, volcanic

explosions, earthquakes, and landslides, to name a

few. Sometimes, as with the Fukushima Daiichi

nuclear reactor accident (Fukushima Daiichi

Accident, 2020), the effect of natural disasters and the

emergencies they cause can be exacerbated by large-

Yamanoor, S., Yamanoor, N. and Thyagaraja, S.

Position Paper: Low-cost Prototyping and Solution Development for Pandemics and Emergencies using Industry 4.0.

DOI: 10.5220/0010147001010108

In Proceedings of the International Conference on Innovative Intelligent Industrial Production and Logistics (IN4PL 2020), pages 101-108

ISBN: 978-989-758-476-3

101

scale incidents such as nuclear reactor meltdowns.

Industrial disasters, such as the Bhopal Gas Disaster

in India, can also cause large-scale medical and

resource constraints (Bhopal disaster, n.d.).

Socially disadvantaged, vulnerable groups and

medically underserved communities lack access to

expensive solutions (UN working to ensure, 2020).

This issue of access extends to businesses and

organizations offering services to and among such

communities. Such access issues can render

operations difficult and allow for continued spread of

infection within and across communities (Johns and

Elsland, 2020).

Even when solutions become available at lower

costs, financial constraints can prevent the

deployment of such solutions (Mills, 2014). While

this is a critical topic of interest, financial

considerations are not detailed in the current work.

Industry 4.0 represents the next wave of

technologies that can be used to combat social

disadvantages across communities. Investment in

STEM Education can provide trained workforce who

can engage in Industry 4.0 (Njogu, J), (Idin, 2018).

Educationally underserved communities face

financial and other resource pressures in being able to

provide STEM education (Ejiwale, 2013). Low-cost

prototypes can be used as tools in educational

pedagogy, both for formal instruction (Yamanoor and

Yamanoor, GHTC, 2017), as well as in the form of

workshops for knowledge sharing and to foment

further private and public research as well as citizen

science, (Yamanoor and Yamanoor, 2017) and the

development of products and solutions to solve

various industrial and societal problems (Yamanoor

and Yamanoor, Workshop, 2018) (Yamanoor and

Yamanoor, 2020, January), (Yamanoor and

Yamanoor, 2020, July).

The position paper describes how Industry 4.0

principles and tools can be employed to rapidly

develop prototypes and solutions while optimizing

for performance and cost by diverse global teams

operating under various constraints and requirements.

The goal is to demonstrate through examples of

ongoing and completed research of the authors that

involve rapidly developed, solutions that are built on

the general principles of Industry 4.0, frugally. These

solutions are then shared for customization, adoption,

and deployment to serve vulnerable, disadvantaged,

and underserved communities everywhere.

2 BACKGROUND

2.1 Indusry 4.0

Industry 4.0 consists of the following principles:

1. Systems in the Industry 4.0 context are cyber-

physical systems, where operations are digitized

and computer-controlled (Cyber-physical

system, n.d.).

2. The Internet of Things (IoT), in the context of

Industry 4.0, is sometimes referred to as the

Industrial Internet of Things (IIoT) is a

significant component of Industry 4.0. Internet

connectivity promotes digital manufacturing

and operations.

Frequently, IIoT and Industry 4.0 are used as

interchangeable terms (Weallans, 2018).

Alternately, they are distinguished. IoT is used

in the consumer context, and IIoT is used in the

industrial context of internet-connected devices.

Internet connectivity allows for data transfer and

control over the internet, enabling live and real-

time actions (IIoT vs., n.d.). The team

distinguishes between IIoT and Industry 4.0.

IIoT is considered an enabling factor of Industry

4.0.

3. Robotics is another critical component in

Industry 4.0. Robots will enable manufacturing

and supply chain operations to be efficient and

optimized. Robots may be used collaboratively,

sometimes termed cobots (Cobot, n.d.). They

can also be used as alternatives to human labour.

4. Additive Manufacturing creates opportunities

within Industry 4.0 for intricate designs, newer

materials and material combinations, production

speed, and optimization of costs. It can serve as

a complement to, and where possible, replace

subtractive manufacturing. Hybrid processes

exist, where the finishing operations are

performed by subtractive techniques (Weiner,

2019). Maintenance, repair, and component

replacement are facilitated by directly

employing Computer Aided Design (CAD)

information to produce components through

additive manufacturing.

Additive Manufacturing is frequently used

interchangeably with the term 3D Printing.

However, with the emergence of 4D Printing

and other paradigms, this interchangeability will

IN4PL 2020 - International Conference on Innovative Intelligent Industrial Production and Logistics

102

be rendered inaccurate (4d printing, n.d.).

Additive Manufacturing presents advantages

such as reduced inventory requirements and

fewer breakdowns and disruptions in the supply

chain (Thomas & Gilbert, 2014). Batch

production can reduce overall costs

(Rickenbacher et al., 2013).

5. Immersive technologies, classified as fully or

semi-immersive technologies, such as Virtual

Reality, Augmented Reality, Extended Reality,

and Mixed Reality can immerse users and

replace or enhance environments with

information to aid in training (Roldan, 2019),

(Longo, Nicoletti & Padovano, 2017),

operations (Wagner, Herrmann, & Thiede,

2017), maintenance (Yew, Ong & Nee, 2017),

troubleshooting (Wolfe, 2019) as well as other

applications.

6. Simulations and Digital Twins, with the

availability of high-performance computing,

will constitute the backbone of Industry 4.0,

allowing for the iterative design of workflows,

training, operations management including

predictive maintenance and servicing, as well as

other applications (Rodič, 2017), (Schluse,

Atorf & Roßmann, 2017). Simulations can be

used for cost reduction, consideration of

alternative designs for part and process flows,

efficiency improvements, and determination

and updates to processes, maintenance, and

service plans.

7. Big Data, a term that has come to encompass

large volumes and variety of data, that can be

processed at very high speeds for possible non-

obvious insights will be a key feature of Industry

4.0 (Witkowski, 2017). Increased deployment of

various forms of sensors, the ability to collect

data continuously during operations as well as

in the background, and the ability to

communicate and analyze the data will create

opportunities for using insights to correct and

improve product and process quality, while

rendering improvements in operational

efficiency, sustainability and other areas (Yan,

Meng, Lu and Li, 2017), (Khan, Wu, Xu & Dou,

2017).

8. Cloud Computing and alternately, Edge

Computing provides the means to analyse the

Big Data that are a consequence of Industry 4.0

(Kim, 2017), (Yen, Liu, Lin, Kao, Wang & Hsu,

2014). Cloud Computing involves the upload of

data to remote servers, where multiple analyses

can be completed, and the results reported

through dashboarding systems. Latency and cost

are primary drawbacks of using cloud

computing in environments where real-time

results are desirable. Edge computing, where the

machine learning aspects are directly integrated

to the location where the data is collected, offers

analytical results in real-time, allowing for

corrections and efficient operations (Trinks &

Felden, 2018), (Ahuett-Garza & Kurfess, 2018).

9. Machine Learning and Deep Learning, both

Probabilistic Artificial Intelligence techniques

are used to recognize patterns and insights from

data (Ghahramani, 2015). Data sources can

include real-time sensory data, synthetic

simulated data, and a mix of different data types,

secured from the various functional elements of

Industry 4.0. When edge computing is

implemented, the results of learning can be

applied in the form of real-time

recommendations for machinery to alter

operations to make error and course corrections

and improve quality and efficiency.

10. Network Connectivity is the backbone of

Industry 4.0 implementations. Various scalable

solutions are available to manage the requisite

communication and data transfer requirements

(IoT Connectivity for, n.d.), (Li, Wan et al.,

2017).

Technologies such as Bluetooth Low Energy can be

used to deploy low-cost solutions within the Industry

4.0 paradigm (Svensson, 2018). The team takes

advantage of such opportunities to reduce

infrastructure costs.

2.2 Industry 4.0 and Team Goals

Industry 4.0 can be used to accrue efficiencies and

cost-savings, which align well with the team’s

objectives of developing low-cost prototypes and

solutions for underserved communities.

In the rapidly evolving COVID-19 pandemic, this

has resulted in a prior accepted publication of a Proof-

of-Concept (PoC) solution developed by the team for

a low-cost non-contact infrared thermometer, with

ongoing research work (Yamanoor, Yamanoor and

Srivastava, in press) followed by a similar solution for

contact thermometry (Yamanoor and Yamanoor, in

press). These works and similar development is

Position Paper: Low-cost Prototyping and Solution Development for Pandemics and Emergencies using Industry 4.0

103

accomplished through multiple elements of Industry

4.0.

1. Projects are aimed at vulnerable, disadvantaged,

and underserved communities, whether they are

personal, industrial, or population-based

projects. Every essential element of the project,

including hardware and software, Bills of

Materials (BOMs), is made available through

open licensing schemes. This is in keeping with

the principles of the Maker Movement (Capps,

2020), (Applin 2020).

2. The objective for all designs and solutions is to

be safe, effective, and as optimal performance at

the lowest total cost. Frugal Engineering

principles must be embraced at all stages of the

project. The products must be manufactured

with sustainable materials and processes

wherever feasible. Digital Prototyping, Direct

CAD to Prototypes, Additive Manufacturing,

and other manufacturing paradigms that are

components of Industry 4.0 allow the team to

minimize iterative development costs.

Efficiencies gleaned through Digital

Manufacturing promote sustainability.

3. Customizability, usability, manufacturability,

scalability, implementation ease, reliability, and

serviceability are vital considerations during

design and development. Simulation and digital

twins are applied to accomplish these goals,

where possible.

4. To scale solutions and reduce variance,

standard, off-the-shelf components and

assemblies are selected when possible. Though

high levels of customization are feasible with

Industry 4.0 (Tom & Veneker, 2019),

minimizing customization can lead to fewer

errors, cost savings, and variations.

3 PROCESSES AND TOOLS

A brief discussion of the processes and tools used by

the team is presented in support of the position that

Industry 4.0 lends both low-cost development and

how low-cost products can be used to implement

Industry 4.0 paradigms to serve underserved

communities.

3.1 Hardware

3.1.1 Compting

The team selects a microcontroller or a single board

computer (SBC) depending on project needs. The

Arduino microcontroller architecture (Arduino –

Home, n.d.) is openly published and inexpensive

clones are available. The Arduino Microcontroller

can be used to prototype as well as implement

affordable Industry 4.0 solutions (Subekti et al.,

2020).

Recently, the team has gained experience using

the Seeeduino XIAO Arduino microcontroller. The

XIAO microcontroller has the smallest footprint in

the family offered by Seeed. List prices range from

$4.90 to $4.30 USD, depending on order quantities

(Seeeduino XIAO, n.d.).

The team’s experience has shown that the smaller

physical and power footprint and computing

capabilities allow it to be useful in Internet of Things

(IoT) and Industrial Internet of Things (IIoT)

projects.

The Raspberry Pi Single Board Computer (Teach,

Learn, n.d.) is a powerful, relatively inexpensive

computer with diverse applications in education,

academic research, and private industry and the

hobby makers movement.

The potential for the deployment of Raspberry Pi

in Industry 4.0 applications has been demonstrated

(Kim & Son, 2018), (Johnston & Cox, 2017). The

team has extensive experience developing projects

with this product line (Yamanoor and Yamanoor,

2015), (Yamanoor and Yamanoor, 2017). At a list

price of $35 USD, it is a very affordable computer

with enough processing power to allow for the design

and implementation of multiple solutions.

The Raspberry Pi Foundation introduced the

Raspberry Pi Zero Single Board Computer, designed

to have a smaller physical footprint, and extremely

affordability around $5 - $10 USD, while still

maintaining robust performance (Buy a Raspberry,

n.d.). The team has used the Raspberry Pi for Proof of

Concept and has successfully replaced it with the

Raspberry Pi Zero during prototyping and later

development stages. Compared to the XIAO and

other microcontrollers, the Pi Zero is best suited for

DC Power consumption, while providing superior

computing and communication capabilities.

The team continues to review and experiment with

other options to review fit against project objectives

and IoT or IIoT applications (Yamanoor &

Yamanoor, IEEE Spectrum, 2017).

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3.1.2 Sensors

Sensors are typically presented on breakout boards

that allow for drop-in testing and development (What

is a breakout, 2015). Breakout boards have several

advantages, including an efficient footprint,

reusability, labelling, documentation, and other

advantages. The availability of affordable sensor

breakout boards has effectively allowed affordable

solutions to be designed for underserved communities

(Patel, 2016).

Recently, the team applied the AMG8833 sensor

breakout board to develop a Proof-of-Concept low

cost non-contact thermometry device for temperature

screening of employees and foot-traffic by industries

in underserved communities. The sensor breakout

board is priced at $39.99 USD (Yamanoor,

Yamanoor, and Srivastava, in press).

3.1.3 Printed Circuit Board Assemblies

Custom Printed Circuit Board Assemblies (PCBAs)

allow for various advantages. Form, fit, and function

can be controlled, and in addition, the circuit can be

optimized for component placement, efficiency, and

costs. Shortcomings include difficulties in iterative

design, lead times, and difficulties in repair and

replacement (Klopotic, 2019).

The team has gained experience working with

low-cost PCBA vendors and has reduced initial and

iterative costs. Aided by remote near-instant quoting

using CAD files and modern batch manufacturing

techniques, vendors such as OSH Park (OSH Park,

(n.d.)) have provided quick turnarounds for traces on

short order-runs at very low costs. The PCBA traces

for the non-contact thermometer, cost $7.55 USD

each, for a short-order run of three items. Industry 4.0

will further drive improvements in PCBA

manufacturing quality, turnaround times and costs.

3.1.4 Enclosures and Related Hardware

The team has used both additive and subtractive

manufacturing for hardware needs, including

enclosures and other structural elements of product

designs. Additive manufacturing, a core element of

Industry 4.0 (Dilberoglu et. al., 2017) has become a

reliable method for most ongoing manufacturing

needs for the team (Yamanoor & Yamanoor,

December 2017). The advantages include the ability

to collaborate remotely, use CAD files eschewing

detailed drawings, and the ability to explore multiple

materials and design alternatives as well as obtain

repeatable, consistent results. The final design

configurations are shared with the public at large for

adoption, meeting one of the team’s core objectives

of open, low-cost design.

3.2 Software

3.2.1 Application Software

Among several languages available for development,

Python has been identified by the team and others as

a suitable language for programming IoT and IIoT

applications (Dasgupta, 2020). The availability of

tutorials, books, code samples, and other features

makes it amenable to develop solutions in Python.

The team has successfully engaged Python in several

projects (Yamanoor & Yamanoor, 2015), (Yamanoor

& Yamanoor, 2017), (Yamanoor & Yamanoor,

2018), (Yamanoor & Yamanoor, 2020) (Yamanoor,

Yamanoor & Srivastava, 2020).

3.2.2 Software for Edge Computing and AI

TensorFlow is an open-source machine learning

platform used for AI applications (TensorFlow, n.d.).

TensorFlow Lite, a lightweight variant, is designed

for microcontrollers. The team has used both tools in

implementations.

The team has worked with other open software

programs such as TinyML for various application

development purposes. Open-source software

solutions have the potential to reduce the cost of

development and implementation of Industry 4.0

solutions. Machine Learning, Deep Learning, and

related techniques have the potential to impact

Industry 4.0, unlike any of its other components.

4 CONCLUSIONS

There are two key positions taken by the team

concerning the Industry 4.0 paradigm encompassing

elements such as additive and digital manufacturing,

smart sensors, cloud computing, machine learning,

and others, elucidated with examples in this work.

1. The elements of Industry 4.0 can be applied to

reduce the cost of developing and implementing

solutions that solve community issues for

underserved and vulnerable communities.

2. The elements of Industry 4.0 can be established to

function inexpensively through the careful

selection of tools and applications. This may

further battles against pandemics, epidemics,

natural and manmade disasters in the future.

Position Paper: Low-cost Prototyping and Solution Development for Pandemics and Emergencies using Industry 4.0

105

5 RECOMMENDATIONS

Industry 4.0 principles can be utilized to combat

pandemics and emergencies. Industry 4.0 elements

can also be applied to alleviate the quality of goods

and services in underserved and vulnerable

communities.

Design and Manufacturing can be distributed and

crowdsourced, with the same quality, globally,

allowing solutions to be implemented among several

communities. Remotely collaborative teams can form

and change, performing speedy, iterative designs, and

implementing solutions.

Combined with sustainable materials and

practices, frugal engineering paradigms, open design

principles, and user-centric customization, a true

revolution can be brought about without prohibitively

expensive infrastructure investments through the

meticulous selection of appropriate tools and

processes. As the technologies mature, there can be a

cascading effect of quality improvements and cost

savings.

Standards should be developed and updated as

needed, for low-cost Industry 4.0 principles. These

standards can guide the creation of baseline pipelines,

allowing for shared infrastructural elements and

designs, further reducing expenses for industries

globally. In future works, the team will be presenting

the outlines for such frugal Industry 4.0 standards.

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