Research Presentation, Rome, 23.10.2023, at 2nd Workshop on Collaborative Process Mining (COMINDS) in connection with 5th International Conference on Process Mining Presentation by Nina Graves Presented Paper: From Identities to Quantities: Introducing Items and Decoupling Points to Object-centric Process Mining Authors: Nina Graves, István Koren, Majid Rafiei, Wil M.P. van der Aalst Abstract: Logistics processes ensure that the right product is at the right location at the right time in the right quantity. Their efficiency is crucial to industrial operations, as they generate costs while not adding value to the product. Process mining techniques improve processes using real-life data. However, the application of process mining to logistics processes poses several challenges, as (1) recorded material movements refer to quantities of items, not individual objects and (2) the required data are often scattered over several systems requiring additional pre-processing efforts. This work presents the concept of item quantities to describe the movement of not individually identifiable items across distributed processes. Subsequently, we introduce a framework to integrate the explicit consideration of item quantities into process mining, consisting of a quantity-related event log and an extension of object-centric Petri nets as a basis for quantity-dependent process analysis. The analysis of an artificial event log demonstrates the additional insights the consideration of quantities uncovers and highlights the potential for the application of process mining in the logistics domain. Author's version of the paper available on ReearchGate: https://www.researchgate.net/publication/375238938_From_Identities_to_Quantities_Introducing_Items_and_Decoupling_Points_to_Object-centric_Process_Mining

1. From Identities to Quantities:
Introducing Items and Decoupling Points to Object-centric
Process Mining
Nina Graves, István Koren, Majid Rafiei, Wil M. P. van der Aalst
Chair of Process and Data Science, RWTH Aachen University, Germany
2rd Workshop on Collaboration Mining for Distributed Systems
5th International Conference on Process Mining (ICPM 2023)
Rome, 23rd October 2023
© Nina Graves (acknowledge when used)

2. Nina Graves, Item Quantities & Decoupling Points
Workshop on Collaboration Mining for Distributed Systems
Rome, 23rd October 2023
2
Quantity-dependent Process
Inventory Management
© Nina Graves (acknowledge when used)

3. Nina Graves, Item Quantities & Decoupling Points
Workshop on Collaboration Mining for Distributed Systems
Rome, 23rd October 2023
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items in stock
Replenishment Process Core Process
Logistics processes deal with quantity-dependent, cross-organisational processes concerning
non-uniquely identifiable items.
Warehouse
customer order
(CO) arrives
pick and pack
items
send parcel
containing items
1
2 3
replenishment
order (RO) arrives
1
items are
delivered
2
© Nina Graves (acknowledge when used)

4. Nina Graves, Item Quantities & Decoupling Points
Workshop on Collaboration Mining for Distributed Systems
Rome, 23rd October 2023
4
(Object-centric) Process Mining heavily depends on the identifiers of the individual objects. It
is not possible to detect the process of objects that are not individually identifiable.
van der Aalst & Berti Discovering Object-centric Petri nets (2020)
OCPNs
• Each place is assigned
to an object type.
• Bindings (“place
bindings”) describes
the tokens of each type
required for firing.
Discovery
• “Following” objects
through the log
• Unique identifiers are
required
© Nina Graves (acknowledge when used)

5. Nina Graves, Item Quantities & Decoupling Points
Workshop on Collaboration Mining for Distributed Systems
Rome, 23rd October 2023
5
Quantity-relationships are distinguished as either a 1:1 relationship or as another type of
relationship. The distinction is made on the type-level.
van der Aalst & Berti Discovering Object-centric Petri nets (2020)
• Normal arcs indicate
that a single token of
this type is required.
• Variable arcs indicate
that it is otherwise.
• Any other quantity-
relationship is not
specified.
© Nina Graves (acknowledge when used)

6. Nina Graves, Item Quantities & Decoupling Points
Workshop on Collaboration Mining for Distributed Systems
Rome, 23rd October 2023
6
Logistics processes deal with quantity-dependent, cross-organisational processes concerning
non-uniquely identifiable items.
replenishment
order (RO) arrives
items are
delivered
items in stock
customer order
(CO) arrives
pick and pack
items
send parcel
containing items
Replenishment Process
1 2
1
2 3
Core Process
Items connecting the processes are not uniquely
identifiable
processes are decoupled
Both processes have a dependency on items in stock
Characteristics
© Nina Graves (acknowledge when used)

7. Nina Graves, Item Quantities & Decoupling Points
Workshop on Collaboration Mining for Distributed Systems
Rome, 23rd October 2023
7
Core Process
Alternative 1 - No identifiers used: Two disconnected object-centric Petri nets.
Place RO
Register
Delivery
Unload
Delivery
Place in
Stock
Replenishment
Order
Delivery
Register
CO
Pick &
Pack
Send
Customer
Order
Parcel
Replenishment Process
© Nina Graves (acknowledge when used)

8. Nina Graves, Item Quantities & Decoupling Points
Workshop on Collaboration Mining for Distributed Systems
Rome, 23rd October 2023
8
Core Process
Alternative 1 - No artificial identifiers used: Two disconnected object-centric Petri nets.
Place RO
Register
Delivery
Unload
Delivery
Place in
Stock
Replenishment
Order
Delivery
Register
CO
Pick &
Pack
Send
Customer
Order
Parcel
Replenishment Process
• disconnected processes
• items not considered
• quantity-dependency not depicted
© Nina Graves (acknowledge when used)

9. Nina Graves, Item Quantities & Decoupling Points
Workshop on Collaboration Mining for Distributed Systems
Rome, 23rd October 2023
9
Alternative 2 – Artificial identifiers used: One connected object-centric Petri net.
Place
RO
Register
Arrival
Unpack
Delivery
Place in
Stock
Register
CO
Pick &
Pack
Send
Replenishment
Order
Delivery
A
B
C
Customer Order
Parcel
Replenishment
Process
Core
Process
© Nina Graves (acknowledge when used)

10. Nina Graves, Item Quantities & Decoupling Points
Workshop on Collaboration Mining for Distributed Systems
Rome, 23rd October 2023
10
Alternative 2 – Artificial identifiers used: One connected object-centric Petri net.
Place
RO
Register
Arrival
Unpack
Delivery
Place in
Stock
Register
CO
Pick &
Pack
Send
Replenishment
Order
Delivery
A
B
C
Customer Order
Parcel
Replenishment
Process
Core
Process
• single process
• redundancy in individual item types
• underspecified quantity-relationships
© Nina Graves (acknowledge when used)

11. Nina Graves, Item Quantities & Decoupling Points
Workshop on Collaboration Mining for Distributed Systems
Rome, 23rd October 2023
11
Quantity-dependent
Process Mining
© Nina Graves (acknowledge when used)

12. Nina Graves, Item Quantities & Decoupling Points
Workshop on Collaboration Mining for Distributed Systems
Rome, 23rd October 2023
12
In addition to objects, items are considered non-identifiable process elements. A decoupling
point refers to a collection of items, indicating a quantity-dependency between two processes.
place
RO
register
arrival
unload
delivery
place in
stock
register
CO pick and
pack
send
parcel
RO
Delivery
CO
Parcel
Warehouse
Decoupling Point indicating a
quantity-dependent decoupling
of sub-processes referring to a
set of item types.
Items
• non-identifiable elements of a process
• items of the same item type are
interchangeable
© Nina Graves (acknowledge when used)

13. Nina Graves, Item Quantities & Decoupling Points
Workshop on Collaboration Mining for Distributed Systems
Rome, 23rd October 2023
13
A decoupling point’s item level can be changed when activities are executed allowing for the
consideration of the item level’s development over time.
place
RO
register
arrival
unload
delivery
place in
stock
register
CO pick and
pack
send
parcel
RO
Delivery
CO
Parcel
Warehouse
Decoupling Points referring to a
collection of non-identifiable items.
Execution of activities increases or
decreases item level of item
collections.
Item
level
time
© Nina Graves (acknowledge when used)

14. Nina Graves, Item Quantities & Decoupling Points
Workshop on Collaboration Mining for Distributed Systems
Rome, 23rd October 2023
14
Firing a transition leads to the execution of a place binding and a quantity binding which
changes the item level of the referenced decoupling points.
𝑡1 𝑡2
𝑑𝑝1
𝑚 𝑑𝑝1 = 𝑎4, 𝑏6, 𝑐2 𝑚 𝑑𝑝2 = 𝑎3
, 𝑏10
, 𝑐7
𝑏1 = (𝑡1, 𝑏𝑝
, 𝑑𝑝1, 𝑎2
, 𝑐 )
𝑏2 = (𝑡2, 𝑏𝑝,
𝑑𝑝1, 𝑎1
, 𝑏2
,
𝑑𝑝2, 𝑏, 𝑐
)
𝑚′
𝑑𝑝1 = 𝑎6
, 𝑏6
, 𝑐3
𝑚′′
𝑑𝑝1 = 𝑎5
, 𝑏4
, 𝑐3
𝑚′′
𝑑𝑝2 = 𝑎3
,𝑏11
, 𝑐8
𝑚′ 𝑑𝑝2 = 𝑎3, 𝑏10, 𝑐7
𝑑𝑝2
executed binding new item level 𝑑𝑝1 new item level 𝑑𝑝2
Item quantities (“negative
multisets”) are used to
describe quantity
operations and item levels.
When a transition fires a place binding and a quantity binding are executed.
© Nina Graves (acknowledge when used)

15. Nina Graves, Item Quantities & Decoupling Points
Workshop on Collaboration Mining for Distributed Systems
Rome, 23rd October 2023
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The corresponding quantity-event log adds a table assigning a quantity operation to a
combination of events and item collections.
• Information on the initial item
levels of the collection points.
• Item quantities describing the
impact events have on a collection
point.
+ initial item
levels
© Nina Graves (acknowledge when used)

16. Nina Graves, Item Quantities & Decoupling Points
Workshop on Collaboration Mining for Distributed Systems
Rome, 23rd October 2023
16
Making use of the initial item levels and the timestamps a sequence of quantity operations can
be considered as a sequence which helps reconstruct item level development.
© Nina Graves (acknowledge when used)

17. Nina Graves, Item Quantities & Decoupling Points
Workshop on Collaboration Mining for Distributed Systems
Rome, 23rd October 2023
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Example Application
© Nina Graves (acknowledge when used)

18. Nina Graves, Item Quantities & Decoupling Points
Workshop on Collaboration Mining for Distributed Systems
Rome, 23rd October 2023
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The data set describes an inventory management process in which different three types of
items are processed and collected.
• Decoupled sub-processes with
a dependency on a collection
point’s item level.
• Three considered item types:
photo albums (a), books (b),
cups (c).
• Loop of customer orders
around pick and pack.
• All events of “place in stock“
add items to 𝑑𝑝1, all events of
“pick and pack“ remove items.
10,050 events, 3,311 objects
© Nina Graves (acknowledge when used)

19. Nina Graves, Item Quantities & Decoupling Points
Workshop on Collaboration Mining for Distributed Systems
Rome, 23rd October 2023
19
The item level of the three item types varies – books have a much larger turnover rate than
cups and albums leading to more frequent deliveries of higher quantities.
• Decrease: “pick and
pack”, increase: “place in
stock”.
• Imbalance between the
number of item removals
and additions; decoupled
sub-processes.
• Varying quantities of the
different item types.
© Nina Graves (acknowledge when used)

20. Nina Graves, Item Quantities & Decoupling Points
Workshop on Collaboration Mining for Distributed Systems
Rome, 23rd October 2023
20
Despite the process being the same for all item types the number of item types per process
execution varies and can be analysed separately.
• Number of required books
broadly spread.
• Average number of items per
customer order:
• 1.3 albums
• 6.9 books
• 0.29 cups
• Turnovers:
• albums: 33 days
• books: 8 days
• cups: 17 days
© Nina Graves (acknowledge when used)

21. Nina Graves, Item Quantities & Decoupling Points
Workshop on Collaboration Mining for Distributed Systems
Rome, 23rd October 2023
21
The consideration of a collection point’s item levels allows for the detection of additional
quantity-related dependencies.
• Bold: Assumed
number of ordered
items.
• Transparent: item level
when “place
replenishment order” is
executed.
• Low variance in the
number of ordered
items
© Nina Graves (acknowledge when used)

22. Nina Graves, Item Quantities & Decoupling Points
Workshop on Collaboration Mining for Distributed Systems
Rome, 23rd October 2023
22
This initial research direction appears to extend process mining’s capabilities and enables
additional support for material flow analysis.
Conclusion
• Current OCPM techniques fail in their consideration of unidentifiable items and
the detection of quantity-dependent process executions.
• The addition of item types and decoupling points allows for the modelling of
decoupled processes as well as the detection of additional quantity-dependent
process insights.
• Event log extraction, tool support and systematic detection of quantity-related
dependencies have yet to be considered.
A promising idea for the application of
process mining to logistics with potential for
further research.
© Nina Graves (acknowledge when used)

23. Thank you very much for your attention!
Also, a big thanks to our reviewers for the valuable feedback!
Nina Graves
graves@pads.rwth-aachen.de
https://www.pads.rwth-aachen.de
© Nina Graves (acknowledge when used)