H O W A H E A T T R E A T I N G P L A N T
E N S U R E S T I G H T P R O C E S S C O N T R O L
A N D E X C E P T I O N A L Q U A L I T Y W I T H I N F L U X D B

• Founded in 1945
• Located near Detroit, Michigan
• Largest commercial rotary heat treat
business in North America
• Serve customers in automotive,
construction, agricultural, aircraft, and
military industries.
• Operates 24 x 7, closing only on major
holidays

W H AT I S H E AT T R E AT I N G ?
Heat treating is any process that uses controlled heating and cooling to modify the
crystalline structure of metals and metal alloys. It allows the material to gain desirable
physical and mechanical properties without altering the shape of the product.
Through hardening (or neutral hardening)
involves heating the material to a temperature
that transforms its internal structure without
melting it. The metal is then held at this
temperature for a period of time, followed by
rapidly cooling (quenching).
Case-hardening is the process of
hardening the surface of a metal part
while allowing the metal deeper
underneath to remain soft, thus forming a
thin layer of harder metal (i.e. case) at the
surface.

Batch or Belt Style Furnace
R O TA R Y R E T O R T F U R N A C E V S
O T H E R C O M M O N T Y P E S O F
F U R N A C E S
Rotary Retort Furnace

R O TA R Y R E T O R T F U R N A C E L I N E
80 ft / 25m
1475 – 1750 °F
(800 - 950 °C)
Feed
System
Washer Furnac
e
Quench
Tank
Not depicted in this sketch:
• Burner system
• Gas flows into furnace
• Quench pumps & cooling
system

E V O L U T I O N T O T H E D I G I T I Z E D H E AT
T R E AT I N G E N V I R O N M E N T
At the outset, ask…
• Does everyone in the organization embrace the value of data?
• What information directly affects quality, maintenance and cost?
• Is everyone willing to invest the time to learn what they do not know and train others?
• Is there a cost ceiling when implementing sensors, databases, software, etc?
• What does everyone in the organization wish they could know about your plant, but
presently do not?

E V O L U T I O N T O T H E D I G I T I Z E D H E AT
T R E AT I N G E N V I R O N M E N T

S I G N A L D ATA

T E M P E R AT U R E & P R E S S U R E
S E N S O R S
Used in furnace, quench tank, generators, heat exchangers, electrical
panels
Type R or Type K
thermocouple,
Pressure Switch,
Digital Pressure
Gauge
Temperature or Pressure
collection device
(Modbus-enabled
controller, Opto22
device, PLC, IOT device,
PC, Raspberry Pi)
Telegraf or Node-RED
running on device or
local computer polls
data every x seconds
Telegraf or
Node-RED
sends data to
InfluxDB every y
seconds.

M O T O R S , V F D ’ S , C O M P R E S S O R S
Used on conveyors, pumps, vibratory feeders, scales, blowers, fans
4-20 mA or 0-10 VDC
signal, RS-232 or
Modbus-enabled device
Signal collection device
(Modbus-enabled
controller, Opto22
device, PLC, IOT device,
PC, Raspberry Pi)
Telegraf or Node-RED running on
device or local computer polls data
every x seconds. Multiple
parameters can be polled:
• Speed (RPM)
• Current draw (amps)
• Direction of rotation
• Temperature
• Alarm codes
Telegraf or
Node-RED
sends data to
InfluxDB every
y seconds.

S I N G L E F U R N A C E C A N
C O N TA I N 3 0 + D ATA P O I N T S

E V O L U T I O N T O T H E D I G I T I Z E D
H E AT T R E AT I N G E N V I R O N M E N T

T H E C O N N E C T E D P L A N T
Everyone has
access to real-time
operational data.

T H E C O N N E C T E D P L A N T, V I S U A L I Z E D

D ATA P R O V I D E S I N S I G H T
Maintenance Activities &
Maintenance Planning
Relationships Between
Product Quality and
Process Data
Understanding Costs &
Control of Costs
Process Monitoring &
Process Alerting
 



A P P LY T O M A I N T E N A N C E
Reactive
“Fix it when
it breaks”
Preventative
Calendar-based
Analytical
Conditions-based
Predictive
Model-based
Effectivenes
s
Efficiency

• How does the thermal effectiveness of a heat exchanger change over time?
TH = join(tables: {th1: th1, th2: th2}, on: ["_time"])
TC = join(tables: {tc1: tc1, tc2: tc2}, on: ["_time"])
TCTH = join(tables: {TC: TC, TH: TH}, on: ["_time"])
|> map(fn: (r) => (r._value_tc2 - r._value_tc1)/(r._value_th1 - r._value_th2))
|> yield(name: "thermal_effectiveness")
F L U X Q U E R I E S F O R
C O N D I T I O N S - B A S E D
M A I N T E N A N C E
Then create alert in Grafana to detect when thermal_effectiveness < x
Ƞ = (tc2 – tc1) / (th1 – th2)

F L U X Q U E R I E S F O R
C O N D I T I O N S - B A S E D
M A I N T E N A N C E
• What is the pressure drop across a filter and how long does it take to become clogged?
|> filter(fn: (r) => r["Port"] == "Inlet" or r["Port"] == "Outlet")
|> filter(fn: (r) => r["_field"] == "Pressure")
|> aggregateWindow(every: 1h, fn: mean, createEmpty: false)
|> pivot(rowKey:["_time"], columnKey: ["Port"], valueColumn: "_value")
|> map(fn: (r) => ({ r with pressure_drop: (r.Inlet - r.Outlet)}))
|> yield(name: "mean")
Then create alert in Grafana to detect when pressure_drop > x
More examples for creating Flux queries to create Grafana alerts here:
https://grafana.com/tutorials/create-alerts-from-flux-queries/

C O S T & C O N S U M P T I O N D ATA

F L U X Q U E R I E S F O R C O S T &
C O N S U M P T I O N
• What is our electrical usage when we are idling our “always on” equipment?
4-Day Thanksgiving Shutdown

F L U X Q U E R I E S F O R C O S T &
C O N S U M P T I O N
• How much more is our electrical usage on the hottest days vs the coldest days?
21-Jun
7.65 MWh
19-Nov
5.88 MWh
21-Jun
96 °F (35.6 °C)
19-Nov
22 °F (-5.5 °C)

S U M M A R Y
• Everyone in the organization must understand & appreciate the value of data
• Evaluate key process parameters that directly affect quality, maintenance and cost
• Organize data logically according to buckets, measurements, fields and tags
• Invest in high quality sensors & devices that are suitable for your environment
• Create signal chains which can be easily diagnosed for problems
• Write meaningful queries & alerts by first asking what the users wish they could know
• Disseminate the data via highly visible dashboards and use the data when diagnosing
problems or troubleshooting equipment or quality issues.