La presentazione del dottor Mario Rapaccini al convegno del 18 aprile 2015 in occasione dell'Innovation Day a Prato presso il Museo del Tessuto.

1. Improving operations:
where, how, when
Mario Rapaccini IBIS Lab, Dip. Ingegneria Industriale, Università di Firenze
ASAP Service Management Forum www.asapsmf.org 1
18 Aprile 2015
Prato, Museo del Tessuto

2. 2Innovation Day, 18 Aprile 2015, Prato – Museo del Tessuto
Fragmentation, personalization and servitization of the
customers’ demand in manufacturing firms lead to higher
complexity in operations management, inside and outside the
firms

3. Industrial revolution timeline: towards
the age of Smart Factories
1st REV.
Introduction of water- and
steam-powered mechanical
manufacturing facilities
End of 18th century Start of 20th century Start of 1970s By now
Introduction of electrically-
powered mass production
based on the division of
labor
first mechanical loom
1784
first assembly line
1870 Cincinnati slaughterhouses
2nd REV.
3rd REV.
first PLC
1969, Modicon 084
4th REV.
Introduction of electronics
and IT to achieve
automation and control of
manufacturing processes
Based on cyber-physical
systems, new technologies and
communication protocols
complexity
time
http://smartfactory.dfki.uni-kl.de/

4. A cyber-physical system (CPS) is a physical object with an embedded system containing
computing power, data storage and network connectivity. Equipped with sensors providing
information about status, environmental and working conditions, as well as with M2M and
M2H communications, CPSs become “Smart Products” that can react to changing
conditions.
Cyber-physical systems
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5. 5Innovation Day, 18 Aprile 2015, Prato – Museo del Tessuto

6. http://www.rethinkrobotics.com
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7. Decentralized control Data-driven operational excellence
Huge amounts of data will be generated upon which
scientists will apply mathematical and statistical expertise.
Advanced analytics will unlock new insights on how to
improve performances and optimize operations along
manufacturing processes.
Each production module will obtain the information
needed to make decisions autonomously. Shop
floor will consist of a network of locally optimizing
decision-making units, and the entire production
environment will self-organize itself through
negotiation mechanisms.
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8. Demand forecasting
Capacity management
Production management
Inventory management
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10. Concluding remarks
 Improving operations
 how: create data lakes and start developing data-driven
decision-support tools and optimisation models
 where: demand forecasting, inventory management,
production planning, order scheduling and sequencing,
 when: by now
 Critical factors:
 do not add artificial complexity due to ill-designed/not
efficient solutions
 people, competence and organization come first, then
technology investments
 align operations management with business strategy or
viceversa
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11. Manifattura Maiano:
audit criticità organizzative, gestionali e
informatiche
Visia Imaging:
supporto al progetto di introduzione del
nuovo sistema informativo: codifica
distinte, prelievi magazzino, ordini, MRP
AOU Meyer
sviluppo e trasferimento soluzione di
pianificazione chirurgica per ottimizzare il
tasso di utilizzo delle sale chirurgiche
Eli Lilly
analisi prestazioni linea di produzione
insulina e sviluppo proposte di
miglioramento
3 M
6 M
9 M
18 M
Timescale of some IBISLAB projects
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12. Mario Rapaccini, Ph.D.
DIEF UNIFI
Mail: mario.rapaccini@unifi.it
Skype: mario_rapaccini,
LinkedIn: Mario Rapaccini
mob. +39 334 6565465
Short biography:
http://www.unifi.it/p-doc-2012-200006-R-3f2a3d31362b31.html
About me
12Innovation Day, 18 Aprile 2015, Prato – Museo del Tessuto

13. Disclaimer
 Il presente documento è stato steso da Mario Rapaccini.
La proprietà intellettuale del documento e di tutti i
contenuti in esso inseriti appartengono esclusivamente
all’autore, se non diversamente specificato.
 Le informazioni contenute in questo documento hanno
valore solo con il commento orale dell’autore.
 L’utilizzo e la riproduzione di questo materiale sono
consentiti solo con il consenso scritto dell’autore.
Eventuali abusi potranno essere perseguiti ai sensi delle
vigenti leggi.
13Innovation Day, 18 Aprile 2015, Prato – Museo del Tessuto