Predictive Maintenance

BIOMASA FORESTAL

BIOMASA FORESTAL

• Galician company located in As Pontes,

dedicated to manufacture and sale of pellets.

• Production capacity: 70.000 T/year.

• High quality product: Pellet Spanish

manufacturer with more quality and

environmental sustainability certifications.

• Commitment to the promotion of the

circular economy in our Community:

supplying raw materials and manufacturing

100% in Galicia

• Strategy focused on innovation and continuous process improvement.

Proof of this are the collaborations with agents of the innovative ecosystem for

the development of R + D + i projects.

PRODUCTIVE PROCESS

• DEBARKING

• SPLINTING

Due to the friction between the trunks,

the bark is released and the wood

passes clean to the next process.

The trunks are reduced to 100 x 100 mm wood

chips.

PRODUCTIVE PROCESS

• RAW MATERIAL GRIDING

The chip obtained in the

previous line goes through the

mill to reduce the particle size

again to 80 x 5 mm.

At this step the humidity is

between 45 – 55%

PRODUCTIVE PROCESS

• DRYING LINE

There is an exchange of heat

between the hot gases coming

from the boiler and the raw

material itself.

As a result, the raw material

reduces its moisture content

from 50% to 10%.

PRODUCTIVE PROCESS

• DRY MATERIAL GRINDING

• GRANULATION

Dry material (10% moisture) is taken

to a second mill to reduce its particle

size again. Shavings are pressed in pellet form with a final

moisture around 5%.

ACTIVA INDUSTRIA 4.0 PILOT

• October 2016: 25 Spanish companies selected to participate in the Active Industry 4.0 Pilot

• November 2016: All the information regarding the situation of the company in terms of business

strategy, processes, organization and people, infrastructures, products and services is analyzed. With

all this, a Situation Diagnosis is prepared.

• February 2017: Starting from the basis of the previous diagnosis, several opportunities are identified

and a it’s defined the Transformation Plan which will take into account the opportunities prioritized in

the previous report.

• March 2017: The execution of the Transformation Plan starts.

• June 2018: Ending of the first phase and starting of the second execution phase

Oct Nov Dic Ene Feb Mar Abr May

Start of the execution Plan

Jun Jul

I4.0 Pilot

Beginning

Diagnosis Transformation

Plan

Workshops

DEFINE AND START THE 4.0 INDUSTRY TRANSFORMATION PLAN

• The first stage of the transformation plan consisted in identifying the opportunities that could solve the

company's improvement points.

• Once identified, an execution proposal and a timeline of the prioritized actions were made.

OPORTUNIDAD dic-16 ene-17 feb-17 mar-17 abr-17 may-17 jun-17 jul-17 ago-17 sep-17 oct-17 nov-17 dic-17 ene-18 feb-18 mar-18 abr-18 may-18 jun-18

Definición Plan

Tecnologías en campa

(stocks y proceso)

Cubierta acopios

material corteza

Secadero inteligente

(Sensorización)

Robotizar carga

producto final

Identificador códigos

saco individual

Desarrollo App

Gestión del cambio.

Formación I4.0

Interoperabilidad entre

sistemas

Optim. sensorización

máquinas/procesos

Innovación:

Colaboraciones

PLANT SENSOR SYSTEM

• Challenge: Obtaining data in real time of the critical parameters of the factory.

• Description: Several types of sensors are installed that transmit information to our production

software (SCADA).

Temperature sensors (PT100, thermocouple and thermographic camera): located in strategic points of the

process, allow us to perform a temperature control of the equipment and gases of the dryer.

Humidity sensors: the moisture of the final product is a quality parameter that requires constant control.

Pressure sensors: allow us to know the flow of air that circulates through the ducts of the dryer.

Spin sensor: detect if there is movement in certain parts of the equipment.

Position detector (limit switches): they allow us to know the position of the mechanical elements.

Level detector (rotary, pendular and ultrasound): report the amount of located material.

Solenoid valves: control the flow of oil to activate the hydraulic cylinders.

Frequency inverters: they allow to vary the speed at which the motor works depending on the load, which

allows an improvement in energy efficiency.

Scales: assess the efficiency of the process by knowing exactly the quantity of raw material used.

This information is processed in the SCADA, where the data analysis, control charts and process adjustments are

made.

AUTOMATION OF PRODUCTION

The information provided by the SENSORS and CONTROL GRAPHS is analyzed, adjusting the process based on

the conclusions obtained.

- Automatic intervention: adjustment of work parameters through the SCADA, without intervention of the

operator.

- Manual intervention: the operator visualize the information in real time and can manually modify some

parameters.

OPTIMIZE DRYING LINE – MAKE IT SMART:

• Challenge: Optimize the dryer process.

• Description: The two dryers have been equipped with the necessary sensors to automate their

operation.

Despite the existing variability in the drying process (weather conditions, characteristics of the raw

material, fuel characteristics, performance of the previous processes ...) we have achieved:

• Maximize production

• Minimize consume (electrical, raw materials ecc)

• Guarantee the final product quality

• Control of the process in real time: immediate detection of deviations (alarms) and fast

intervention to return to normal operating parameters

BOILER Fireplace Temp, Exit Temp, Fuel feed, Fan speed, Gas flow…

DRYER Work Temp, Pressure, Raw material Humidity, Fueling Speed…

NEW CHALLENGE 2018 – 2019:

PREDICTIVE MAINTENANCE

• Overview: The factory works 24h, 365 days per year, which implies that an unexpected stop has

great implications. Nowadays we make two types of maintenance:

- Corrective maintenance: when a failure is detected or there is an unexpected stop of the

equipment

- Preventive maintenance: visual checks, tighten the screws, lubrication; according to fabricant

directions or maintenance team experience.

• Challenge: Reduce unscheduled stops

• Description: The objective is to analyze and exploit the available data which are production

variables and historical equipment failures in such a way that we detect patterns that help us to

predict anomalous behavior of the equipment, anticipating possible failures.

NEW CHALLENGE 2018 – 2019:

PREDICTIVE MAINTENANCE

1. IDENTIFY THE CRITICAL PATH

Debarking Splinting Raw material

grinding Boiling

Drying Dry material

grinding Granulation Storage

NEW CHALLENGE 2018 – 2019:

PREDICTIVE MAINTENANCE

1. IDENTIFY THE CRITICAL PATH

Debarking Splinting Raw material

grinding Boiling

DRYING Dry material

grinding Granulation Storage

The DRYING LINE will be considered as the SCOPE of this project, since the impact of a

possible failure in production is highly critical and, in addition, the complexity of the process

makes it difficult to detect possible failures or wear on the equipment.

NEW CHALLENGE 2018 – 2019:

PREDICTIVE MAINTENANCE

2. COLLECT DATA DRYER

• Scada: Historical data file of representative variables

• Manual: Most significant production data filled by the operator)

• ERP: Preventive maintenance + workshop orders + costs applied to equipment

NEW CHALLENGE 2018 – 2019:

PREDICTIVE MAINTENANCE

2. COLLECT DATA DRYER

• Scada: Historical data file of representative variables

• Manual: Most significant production data filled by the operator

• ERP: Preventive maintenance + workshop orders + costs applied to equipment

NEW CHALLENGE 2018 – 2019:

PREDICTIVE MAINTENANCE

2. COLLECT DATA DRYER

• Scada: Historical data file of representative variables

• Manual: Most significant production data filled by the operator)

• ERP: Preventive maintenance + workshop orders + costs applied to

equipment

NEW CHALLENGE 2018 – 2019:

PREDICTIVE MAINTENANCE

3. IDENTIFICATION OF SOURCES OF VARIABILITY

• Raw material initial humidity

• Fuel humidity (bark)

• Climatology: temperature and humidity

• Hot air flow controlled by the pressure applied inside the dryer

• Raw material flow controlled by feeding speed and stopping times of the mobile

base

• Equipment conditions as the wear produces a loss of performance in the equipment

NEW CHALLENGE 2018 – 2019:

PREDICTIVE MAINTENANCE

4. IDENTIFICATION OF PATTERNS AND MATHEMATICAL MODEL

• Experience:

Indicators that conducts are damage: reduction of the production, the system

demands higher temperatures and depressions

Dryer’s Performance drops when the material is accumulated on conducts wall.

• SCOPE: Model the performance of the dryer in order to determinate the normal

conditions.

By doing so, when production differs from the values considered normal, a stop can

be scheduled to carry out the pertinent repairs.

¡THANK YOU FOR YOUR ATTENTION!

www.bioforestal.es

Laura Vázquez Pardo

laura.vazquez@grupogestan.net