Value Proposition for Smart Retroﬁt Solutions

Aditya Mairal, Michael Muller and Todd Rossi

Center for Advanced Energy Systems, Rutgers University, New Jersey, U.S.A.

Keywords:

Smart Retroﬁtting, IIoT, Value Proposition Matrix, Low-hanging Fruit Applications.

Abstract:

Smart retroﬁtting can include automation, simulation, data collection and optimization of manufacturing pro-

cesses. It is strongly coupled with the concept of Industrial Internet of Things (IIoT). The adoption of smart

retroﬁtting in manufacturing is found to be modest despite their beneﬁts. Lack of structured value proposition

approach by application is suspected as one of the major reasons for lower adoption. This paper provides a

value proposition matrix and applies the same to ten low-hanging fruit smart retroﬁt applications. This would

provide a framework for understanding the full value a smart retroﬁt applications can provide. The matrix can

also be used to rank the smart retroﬁt solutions.

1 INTRODUCTION

Smart retroﬁtting in manufacturing is deﬁned as “the

integration of new technologies and sensors into

legacy systems, supporting the transition towards

smart manufacturing. It can extend the life cycle of

machinery and equipment in a way that is feasible,

time-saving, and requires comparatively low invest-

ments” (Jaspert et al., 2021). (Kusiak, 2018) suggests

that smart manufacturing goes beyond shop-ﬂoor au-

tomation and involves autonomy, evolution, simula-

tion, optimization of the manufacturing enterprise.

IIoT (Industrial Internet of Things) plays a signiﬁcant

role in achieving these. IIoT consists of collecting

and integrating process data; and ﬁnding patterns to

achieve better quality control, productivity, and the

speed of operation(Vrana, 2021). IIoT also allows for

augmented controls, meaning that the alarms and set-

points for the control mechanisms can be made dy-

namic based on the data collected(Smith, 2017).

In the full-text analysis of existing literature

(Jaspert et al., 2021), ensuring competitiveness and

increasing equipment efﬁciency are identiﬁed as

the most mentioned contextual drivers of smart

retroﬁtting and limited resources, high complexity, di-

verse requirements, and cultural restraints are iden-

tiﬁed as key challenges in the decreasing order of

occurrences in the dataset. The paper also cate-

gorizes beneﬁts of smart retroﬁtting into four cat-

egories: sustainability, practicability, functionality,

and compatibility. The beneﬁts in each category

that are mentioned most often are maintaining legacy

systems, providing low-cost solution, enabling as-

set transparency, and upgrading to new technologies.

However, the analysis also suggests that there is a

gap in understanding “strategic advantages of smart

retroﬁtting” and “potential beneﬁts to the end cus-

tomer”. The authors conclude that “functional and

value-creating beneﬁts are rarely addressed”.

Similar observations were made after analyzing

several Industrial Assessment Center (IAC) recom-

mendations. IACs carry out energy audits at small

and medium sized manufacturers to give recommen-

dations around improving energy and production ef-

ﬁciencies. The IAC recommendations show that the

adoption of smart retroﬁt solutions is modest despite

their beneﬁts. Lack of structured value proposition

approach by application, and higher payback period

are speculated as the major reasons for lower adop-

tion. This paper intends to address these challenges

by developing a matrix for value proposition of smart

retroﬁt solutions and applying it to rank ten “low

hanging fruit” applications. Further high value ap-

plications involving variable frequency drives is dis-

cussed in more detail.

2 VALUE PROPOSITION

CATEGORIES

Smart retroﬁt solutions can be ranked by using the

below mentioned categories (Fantana et al., 2013):

1. Visibility into the manufacturing process perfor-

Mairal, A., Muller, M. and Rossi, T.

Value Proposition for Smart Retroﬁt Solutions.

DOI: 10.5220/0011070000003203

In Proceedings of the 11th International Conference on Smart Cities and Green ICT Systems (SMARTGREENS 2022), pages 125-129

ISBN: 978-989-758-572-2; ISSN: 2184-4968

125

mance by collecting the operating condition data.

2. Performance Improvement by optimizing and

utilizing the equipment better, optimizing ﬂows,

reducing production losses.

3. Quality Improvement using a feedback loop

which would measure the product quality and then

tweak the operating conditions to improve the

same.

4. Reduced Energy Consumption by operating the

equipment with minimum energy use.

5. Improved Maintenance by condition-based

monitoring, data collection on system operating

condition and subsequent data analysis.

6. Robustness/Reliability includes clear and unam-

biguous parameter measurement, less false posi-

tives, fewer or no re-calibrations required and the

solution that allows for continuous operation of

industrial processes.

7. Reasonable Cost includes the cost vs. beneﬁt

analysis rather than the absolute cost of the IIoT

solution.

3 SMART RETROFIT: LOW

HANGING FRUIT

OPPORTUNITIES

The potential smart retroﬁt beneﬁts range from

higher equipment effectiveness to achieving better

performance. These beneﬁts depend heavily on

the application for which smart retroﬁt solutions

are implemented. Some potential smart retroﬁt

applications that fall under the “low hanging fruit”

category, meaning applications for which smart

retroﬁt IIoT solutions are more easily implemented,

are as described below:

• Adjustable Speed Drives in Industrial Mixing:

The central idea is to operate the industrial mix-

ing motors by reducing the initial speed to avoid

power spikes. One of the methods to accom-

plish this is to use a variable frequency drive to

control the speed of motor based on a maximum

power requirement. As the speed of mixing in-

creases, the mixture warms up reducing the vis-

cosity and thereby the torque requirement, which

in turn would reduce the power required from the

motor. There is also a possibility of measuring

and assessing the product quality through its vis-

cosity and temperature as represented by the re-

quired torque.

• Compressed Air Energy Management: In-

stalling pressure, air ﬂow rate and current trans-

ducer sensors on compressed air system can help

analyze and report performance of the system.

This data can be used to assess air leaks, opti-

mize multiple compressor part load performance,

and avoid short cycling and ﬂow spikes. In ad-

dition, compressed air dryer system performance

can be monitored by measuring the overﬂow wa-

ter collected in downstream tank and/or air out-

let dewpoint. This detects water pass through and

reports performance to create trends and support

troubleshooting procedures.

• Intelligent Bag House Fan Control: This ap-

plication consists of implementing an on-demand

system for baghouses. The system would main-

tain the required suction pressure based on the ac-

tivity of the workstations and use a variable fre-

quency drive to adjust the speed of the baghouse

blower. Such an operation would result in running

the blower at lower than full-load capacity as re-

quired. The blower speed is efﬁciently controlled

by changing the frequency of voltage provided to

the motor instead of using other methods such as

valves and dampers.

• Energy Storage Intelligence: The application

consists of measuring and reporting the equip-

ment performance for energy storage units like

batteries or ice storage. These measurements can

be used to charge (e.g. solar) when the energy is

available or inexpensive and discharge to reduce

electricity demand and TOU charges

• Cooling Tower “Free Cooling” Intelligence:

Using the cooling tower water to cool the process

ﬂuid helps reduce the load from the chiller sys-

tem partially or completely depending on the am-

bient temperature. Performance can be optimized

by adjusting the parallel free cooling and chiller

loops.

• Smart Condensate Return Tank: By measur-

ing the make-up and feed water ﬂowing through

a boiler condensate tank, condensate return and

boiler loads can be tracked and steam trap prob-

lems can be detected to reduce water treatment

costs and leaks. Boiler performance can also be

visualised for better troubleshooting and perfor-

mance optimization.

• Production Line “Quick Change” Monitor-

ing: The goal is to minimize product change-out

time. IIoT solutions can be used to know the

changeover/change out time from machine load

data. This data can also be used to provide in-

sights around overall equipment effectiveness in

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126

addition to improving product sequencing, pro-

ductivity, changeover times and energy use per

unit delivered product.

• Motor-driven System Performance: Avoid fail-

ures, downtimes and resolve problems before

they happen by monitoring temperature, vibra-

tion, and/or electric motor pattern. This would

be applicable to any motor driven system which

is critical for plant operation

• 15-minute Demand Data Analysis: Energy

spikes can be assessed and better sequencing can

reduce demand charges by monitoring 15-minute

interval data. Correlation between demand data

and shifts, operations, seasons etc. can also be

obtained.

• Coordinating HVAC Compressor Loads: The

idea is to adjust setpoints with IIoT thermostats

for coordinating multiple HVAC compressors.

This can not only save on energy demand and en-

ergy use but can also provide automated response

to failures and degradation.

4 VALUE PROPOSITION MATRIX

FOR LOW-HANGING FRUIT

OPPORTUNITIES

The value proposition of the above-mentioned smart

retroﬁt “low-hanging fruit” applications is ranked as

shown in Table 2 below. The value categories are con-

sidered having equal weights. The boxes in value

proposition matrix are checked when that value is

achieved by the application. The ease of quantifying

the beneﬁts each value category provides is another

factor, which is considered, and the classiﬁcation is

shown in Table 1

Table 1: Ease of Quantiﬁcation.

Value Categories

Quantiﬁcation

Easy Medium Hard

Visibility x

Performance

Improvement

Quality Improvement x

Reduced Energy

Consumption

Improved Maintenance x

Robustness/Reliability x

Reasonable cost x

5 DISCUSSION

The value proposition matrix provides a potential ap-

proach towards understanding the value provided by

an IIoT solution, categorize the same and rank the

ideas based on how many boxes are checked. In

the ﬁgure, the application with more than 75% boxes

checked is categorized as a high value proposition,

the one with more than 50% but less than 75% boxes

checked is categorized as a medium value proposition

and the rest as a low value proposition solution. Vari-

able speed drive applications and coordinating HVAC

compressor loads have most boxes checked.

Implementing IIoT retroﬁt solutions for all the ap-

plications listed above would enable visibility into the

process as the control action is coupled with operating

parameters, for instance: Motor driven system per-

formance measures various parameters like tempera-

ture, vibration, electric current or power etc. Com-

pressed air management measures datapoints such as

pressure, air ﬂow rate and water pass through.

All the applications would save energy as well.

By monitoring motor driven system performance and

HVAC compressor loads, it is possible to improve

maintenance as they enable condition-based monitor-

ing. Applications such as compressed air energy man-

agement, smart condensate return tank, cooling tower

free cooling allows for performance improvement op-

portunities as well. In the case of compressed air

management, multiple compressor part loads can be

optimized whereas in case of smart condensate tank

return leaks can be detected and ﬁxed to improve

the boiler performance. Free cooling loop in cooling

tower gives an opportunity to optimize the operation

between chiller and free cooling loops based on the

ambient temperature and process requirements.

The applications like smart condensate return and

HVAC compressor loads use simple and cost-effective

sensors to monitor the parameters. Since the motor

driven system performance application involves more

sensors and complicated data analysis it is subject

to more false positives. Hence in the value proposi-

tion matrix robustness is not considered as the value

proposition for the same.

5.1 High-value Retroﬁt IIoT Solutions

5.1.1 VFDs

Variable Frequency Drive is a type of motor drive

that controls the speed and torque of an AC motor by

varying the motor input frequency. The two appli-

cations discussed here are using VFDs for industrial

mixing and smart baghouse systems. In both these

Value Proposition for Smart Retroﬁt Solutions

127

Table 2: Value Proposition Matrix.

High-value

IIoT

Applications

Visi-

bility

Perfor-

mance

Improv-

ement

Quality

Impro-

vement

Reduced

Energy

Consum-

ption

Improv-

Maint-

enance

Robust-

ness/

Reliab-

ility

Reaso-

nable

Cost

Overall

Value

Adjustable

speed drives

in industrial

mixing

x x x x x x 86% High

Compressed

air energy

management

x x x x 57%

Med-

ium

Intelligent

bag house

fan control

x x x x x x x 100% High

Energy storage

intelligence

x x 29% Low

Cooling tower

“Free Cooling”

Intelligence

x x x 43% Low

Smart condensate

return tank

x x x x x 71%

Med-

ium

Production line

“Quick Change”

monitoring

x x x 43% Low

Motor-driven

system

performance

x x x x 57%

Med-

ium

15-minute

demand data

analysis

x x 29% Low

Coordinating

HVAC

compressor

loads

x x x x x x 86% High

applications visibility into the process is obtained. In

Industrial mixing application the speed of motor is

controlled based on power requirement which in turn

is based on mixture viscosity and temperature. In

Smart baghouse the speed of suction fan is controlled

by sensing the pressure requirement at each station

which in turn indicates how many stations are run-

ning.

Performance improvement can be obtained in case

of baghouse by optimizing the suction required at dif-

ferent stations. Other process improvements in the

form of saved conditioned air can also be achieved.

In absence of a VFD, the baghouse suction would also

remove the conditioned air from the space in turn in-

creasing the load on the HVAC system. For processes

like paint sprays booths and furnaces, implementing

a VFD on baghouse suction would enable optimiza-

tion of process parameters like furnace temperature

and paint spray pressure to achieve process fuel sav-

ings.

Quality improvement can be achieved in industrial

mixing by tightly controlling the viscosity and tem-

perature of the mixture by controlling the speed of

motor. In the baghouse application, as soon as the

workstation is sensed to be active, the baghouse suc-

tion would start to remove any dust, mist, gases and

maintain product quality. Energy consumption is re-

duced when partly loaded motors are retroﬁtted with

a VFD.

Smart baghouses measure the differential pressure

across the workstations and the ﬁlters. This would al-

low for condition-based monitoring and maintenance.

In the case of industrial mixing since the operating

parameters like viscosity, temperature, torque and/or

velocity are monitored, they can be used to detect

anomalies. The baghouse VFD solution is robust

SMARTGREENS 2022 - 11th International Conference on Smart Cities and Green ICT Systems

128

since the parameters like pressure and/or air ﬂow can

be measured with high accuracy, and the relation to

other process parameters is well deﬁned. For VFDs

in baghouse a payback period of lower than 1 year

can be achieved (ref, ).

6 CONCLUSION

A lack of structured approach towards value propo-

sition of smart retroﬁt solutions was suspected as the

reason for their lower adoption. Hence, in this paper,

a value proposition matrix was presented and applied

to ten “low-hanging fruit” smart retroﬁt solutions.

Variable frequency drive applications were discussed

in detail as one of the high-value smart retroﬁt appli-

cations. The applications were evaluated without con-

sidering the limitations of smart retroﬁts /IIoT such as

cybersecurity. All the categories in the value propo-

sition matrix were considered having equal weights.

However, based on application certain beneﬁt cate-

gories may out-weigh the other and more studies are

required to understand the same.

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129