Maintenance Management

Pavan Headquarters – Galliera Veneta (PD) – Italy

25 March29 March 2019

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Class overview

A COURSE THAT PROVIDES SAVINGS AND EFFICIENCY

Contents


The maintenance of industrial plants is an increasingly strategic asset: the efficiency and productivity of the entire supply chain depend on it! Thanks to the intervention of highly competent and specialized technicians, this course will allow you to learn and experience the most advanced techniques to manage the maintenance of the plants, in particular for the production of dry pasta and extruded products. It will deal not only with the best practices for a correct ordinary maintenance, but also with the most advanced solutions that allow preventive intervention on the plant to guarantee its good functioning in time, avoiding production interruptions or drops in performance. A proper maintenance therefore means a reduction in overall management costs and fewer operating problems.

The presentations will be complemented by practical examples thanks to the collaboration with Pastificio Campioni (Italy), a high-tech pasta factory exclusively equipped with Pavan lines, which has allowed us to carry out complete and detailed technical investigations.


The seminar will focus on:
> Big Data for a manufacturing 4.0.
> Predictive maintenance techniques:
meaning, objectives, application mode, cost/benefit analysis;
> Maintenance management:
programming; document management; preventive, predictive and proactive maintenance application; warehouse management; KPIs
> Maintenance of pasta production plants.

Duration

5 Days, 25 – 29 March – 2019

Language

English.

(The course may be available in other languages depending on the total number of applicants for a given language).

Target

Plant Managers, Production Managers, R&D Managers, Quality Control Managers, Production Engineers.

Our speakers

Luca Girelli

 

Andrea Spadacini

Endress+Hauser Italia

Francesco Fico

Endress+Hauser Italia

Giorgio Grandi

Michell Instruments

Veronica Brizzi

 

Stefano Bianchi

Kluber

Andrea Bertini

GEA

Roberto Chimetto

Pavan Head of Technical Assistance

Antonio Liviero

Pavan Technical Assistance

What’s included

The course package includes mentioned services from Sunday, March 25th evening and to Friday,March 29th afternoon.

VALUE

40 hours of classes, attendance to all training sessions, trials, sensory tests; access to all presentations; proceedings articles

CERTIFICATE

Certificate of Food Tech Master status

ACCOMMODATION

4 stars Hotel accommodation

MEALS

Breakfast, coffee break, lunch and dinner

TRANSFER

from/to Venice Airport;
daily transfers from hotel to Pavan Headquarters and back;
transfers in the evening for dinner, when necessary

AFTER WORK

Guided city tours in the evening
(tours may be cancelled in case of bad weather)

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Daily programme

The program and the topics of the courses may be subject to change.

March

25

Maintenance Management:
• Defining goals to be achieved based on weak points and maintenance requirements
• Documents management
• Programming routine and extraordinary maintenance and related inspections
• Preventive maintenance
• Predictive maintenance
• Proactive maintenance
• Spare parts and stock management
• The role of staff training in skills development
• Adopting system to measure the effectiveness and key indicators: maintenance KPIs
• Q&A

Function, calibration and maintenance of dough level probes and flow meters

March

26

Predictive maintenance techniques:
• Overview on different maintenance concepts
• Introduction on predictive maintenance
• Vibration analysis
• Lubricants analysis
• Infrared thermography
• Ultrasound analysis
• Analysis of electric motors
• Non-destructive test techniques
• Practical application exercises
• Maintenance self-diagnostics
• How to draw up a cost/benefit analysis
• Q&A

Function, calibration and maintenance of Rotronic probes

March

27

Big Data for a manufacturing 4.0
• Data analysis to assess process quality
• Using data to create a baseline of reference
• Analysis of the variable(s) that identify the quality of the process
• Identification of the parameters that influence the value of the variables of the first point – correlation matrix
• Definition of the process to be evaluated
• Implementation of a predictive model for the evaluation of the defined variable and validation
• Identification of periods with efficient or less efficient behavior based on data history
• Data analysis to evaluate machine downtime
• How to collect data from machines and how to analyse them
• What infrastructures are needed to collect data from machines, analyse and valorise them
• How to analyze production process variables to develop quality or performance predictive analysis
• How to evaluate internal capabilities
• What infrastructure, equipment and resources are needed?
• How to find the necessary external capabilities
• Specific examples in the food production sector


Efficiency and maintenance of centrifugal pumps: how to choose a centrifugal pump, typical curves of a pump, behavior at starting, operating and adjustment status, maintenance and troubleshooting


Practical experiences on the management of maintenance techniques

March

28

Big Data for a manufacturing 4.0
• Data analysis to assess process quality
• Using data to create a baseline of reference
• Analysis of the variable(s) that identify the quality of the process
• Identification of the parameters that influence the value of the variables of the first point – correlation matrix
• Definition of the process to be evaluated
• Implementation of a predictive model for the evaluation of the defined variable and validation
• Identification of periods with efficient or less efficient behavior based on data history
• Data analysis to evaluate machine downtime
• How to collect data from machines and how to analyse them
• What infrastructures are needed to collect data from machines, analyse and valorise them
• How to analyze production process variables to develop quality or performance predictive analysis
• How to evaluate internal capabilities
• What infrastructure, equipment and resources are needed?
• How to find the necessary external capabilities
• Specific examples in the food production sector


Tribology techniques: Gear oil lubrication, bearings lubrication, selecting the correct gear oil, replacing oil and grease.

March

29

Routine and extraordinary maintenance of dry pasta production lines

Contents
• Data analysis to assess process quality
• Using data to create a baseline of reference
• Analysis of the variable(s) that identify the quality of the process
• Identification of the parameters that influence the value of the variables of the first point – correlation matrix
• Definition of the process to be evaluated
• Implementation of a predictive model for the evaluation of the defined variable and validation
• Identification of periods with efficient or less efficient behavior based on data history
• Data analysis to evaluate machine downtime
• How to collect data from machines and how to analyse them
• What infrastructures are needed to collect data from machines, analyse and valorise them
• How to analyze production process variables to develop quality or performance predictive analysis
• How to evaluate internal capabilities
• What infrastructure, equipment and resources are needed?
• How to find the necessary external capabilities
• Specific examples in the food production sector

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Join the course and learn how to optimize the yield of your production lines over time!

Mar

25

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26

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27

Mar

28

Mar

29

Maintenance Management

Pavan Headquarters – Galliera Veneta (PD) – Italy

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