execution sequences to identify equivalent treatments over the different objects being produced in each execution. P. Viale, N. Benayadi, M. Le Goc, J. Pinaton.
Outline Introduction Extension of TOM4L Approach for Process Mining Application Conclusion and Future Work
USING THE TOM4L APPROACH AND SEQUENCE ALIGNMENT INFORMATION FOR MODELING LARGE SCALE MANUFACTURING PROCESS Pamela Viale1,2 , Nabil Benayadi1 , Marc Le Goc1 , Jacques Pinaton2
1 LSIS
- Laboratoire des Sciences de l’Information et des syst` e mes Marseille, France
2 STMicroelectronics
Rousset, France
ICEIS 2010 8 - 12 June, Funchal, Madeira - Portugal P. Viale, N. Benayadi, M. Le Goc, J. Pinaton
Modeling Large Scale Manufacturing Process
Outline Introduction Extension of TOM4L Approach for Process Mining Application Conclusion and Future Work
1
Introduction
2
Extension of TOM4L Approach for Process Mining Class of Equivalence Process Phase Potential Cycles Modeling a Large Scale Process
3
Application Modeling STMicroelectronics’ Manufacturing Processes
4
Conclusion and Future Work Conclusion Future Work
P. Viale, N. Benayadi, M. Le Goc, J. Pinaton
Modeling Large Scale Manufacturing Process
Outline Introduction Extension of TOM4L Approach for Process Mining Application Conclusion and Future Work
Introduction
Modeling manufacturing processes for the construction of complex objects like electronic chips is crucial for maximizing productivity The methods and the algorithms developed in the Process Mining domain aims at modeling such manufacturing processes with graphs of manufacturing steps (treatments, operations or tasks) from the timed messages contained in the database The proposed algorithms generally generate complex models that are difficult to read and interpret when the process contains hundred of steps
P. Viale, N. Benayadi, M. Le Goc, J. Pinaton
Modeling Large Scale Manufacturing Process
Outline Introduction Extension of TOM4L Approach for Process Mining Application Conclusion and Future Work
Introduction
We propose a modeling method and the corresponding algorithms to model manufacturing processes having hundreds of steps. Our method is based on cutting the sequences in subsequences called process phases. The way of cutting the sequences is based on information obtained from an alignment between them. However, finding an appropiate sequence alignment is not a simple task.
P. Viale, N. Benayadi, M. Le Goc, J. Pinaton
Modeling Large Scale Manufacturing Process
Outline Introduction Extension of TOM4L Approach for Process Mining Application Conclusion and Future Work
Introduction TOM4L Approach
The TOM4L Approach1 for discovering temporal knowledge from timed observations provides a general framework for modeling dynamic processes that is based on a markovian representation but uses abstract chronicle models instead of finite state machines This framework considers that the timed messages of a series are written in a database by a program, called a monitoring cognitive agent MCA, that monitors a production process Pr . A timed message is represented with an occurrence of a discrete event class C i = {ei } that is an arbitrary set of discrete event ei = (xi , δi ), where δi is one of the discrete value of the variable xi . 1
Timed Observations Mined for Learning, previously called Stochastic Approach P. Viale, N. Benayadi, M. Le Goc, J. Pinaton
Modeling Large Scale Manufacturing Process
Outline Introduction Extension of TOM4L Approach for Process Mining Application Conclusion and Future Work
Introduction TOM4L Approach
A sequence of discrete event class occurrences is then considered as the observable manifestation of a series of state transitions in a timed stochastic automaton representing the couple (Pr , MCA). The BJT4G algorithm represents a set of sequences of discrete event class occurrences with a one order Markov chain and uses an abductive reasoning to identify the set of the most probable timed sequential binary relations between discrete event classes leading to a given class We propose an extension of the TOM4L Approach for modeling Large Scale Manufacturing Processes P. Viale, N. Benayadi, M. Le Goc, J. Pinaton
Modeling Large Scale Manufacturing Process
Outline Introduction Extension of TOM4L Approach for Process Mining Application Conclusion and Future Work
Class of Equivalence Process Phase Potential Cycles Modeling a Large Scale Process
Extension of TOM4L Approach Class of Equivalence
By definition, a large scale process contains a lot of steps. Some steps differs in some characteristics but realizes similar treatments. Equivalence Class Definition Given a set of sequences Ω = {ωi • i = 1 . . . n} of event class ocurrences. A set of event classes that have the same before and after relations can be replace by an equivalent class. Ci
C1
Co
Ci
CE
Co
C2 C E = {C 1 , C 2 , C 3 } C3
P. Viale, N. Benayadi, M. Le Goc, J. Pinaton
Modeling Large Scale Manufacturing Process
Outline Introduction Extension of TOM4L Approach for Process Mining Application Conclusion and Future Work
Class of Equivalence Process Phase Potential Cycles Modeling a Large Scale Process
Extension of TOM4L Approach Process Phase
Usual controls in production sometimes show that certain objects did not achieved the expected characteristics. Some actions (special actions) has to be done to correct the problem. These actions usually consist on performing special treatments and/or the repetition of tasks. This is the reason why we need to align the different process execution sequences to identify equivalent treatments over the different objects being produced in each execution.
P. Viale, N. Benayadi, M. Le Goc, J. Pinaton
Modeling Large Scale Manufacturing Process
Outline Introduction Extension of TOM4L Approach for Process Mining Application Conclusion and Future Work
Class of Equivalence Process Phase Potential Cycles Modeling a Large Scale Process
Extension of TOM4L Approach Process Phase
Imagine these two sequences are executions of the a same process (the final product is the same even though one sequence is longer than the other one):
CE
CE
P. Viale, N. Benayadi, M. Le Goc, J. Pinaton
CE
CE
CE
Modeling Large Scale Manufacturing Process
Outline Introduction Extension of TOM4L Approach for Process Mining Application Conclusion and Future Work
Class of Equivalence Process Phase Potential Cycles Modeling a Large Scale Process
Extension of TOM4L Approach Process Phase
Imagine these two sequences are executions of the a same process (the final product is the same even though one sequence is longer than the other one):
CE
CE
P. Viale, N. Benayadi, M. Le Goc, J. Pinaton
CE
CE
CE
Modeling Large Scale Manufacturing Process
Outline Introduction Extension of TOM4L Approach for Process Mining Application Conclusion and Future Work
Class of Equivalence Process Phase Potential Cycles Modeling a Large Scale Process
Extension of TOM4L Approach Process Phase
Imagine these two sequences are executions of the a same process (the final product is the same even though one sequence is longer than the other one):
CE
CE
P. Viale, N. Benayadi, M. Le Goc, J. Pinaton
CE
CE
CE
Modeling Large Scale Manufacturing Process
Outline Introduction Extension of TOM4L Approach for Process Mining Application Conclusion and Future Work
Class of Equivalence Process Phase Potential Cycles Modeling a Large Scale Process
Extension of TOM4L Approach Process Phase
Imagine these two sequences are executions of the a same process (the final product is the same even though one sequence is longer than the other one):
CE
CE
P. Viale, N. Benayadi, M. Le Goc, J. Pinaton
CE
CE
CE
Modeling Large Scale Manufacturing Process
Outline Introduction Extension of TOM4L Approach for Process Mining Application Conclusion and Future Work
Class of Equivalence Process Phase Potential Cycles Modeling a Large Scale Process
Extension of TOM4L Approach Process Phase
Imagine these two sequences are executions of the a same process (the final product is the same even though one sequence is longer than the other one):
CE
CE
P. Viale, N. Benayadi, M. Le Goc, J. Pinaton
CE
CE
CE
Modeling Large Scale Manufacturing Process
Outline Introduction Extension of TOM4L Approach for Process Mining Application Conclusion and Future Work
Class of Equivalence Process Phase Potential Cycles Modeling a Large Scale Process
Extension of TOM4L Approach Process Phase
Imagine these two sequences are executions of the a same process (the final product is the same even though one sequence is longer than the other one):
Corrective actions CE
CE
P. Viale, N. Benayadi, M. Le Goc, J. Pinaton
CE
CE
CE
Modeling Large Scale Manufacturing Process
Outline Introduction Extension of TOM4L Approach for Process Mining Application Conclusion and Future Work
Class of Equivalence Process Phase Potential Cycles Modeling a Large Scale Process
Extension of TOM4L Approach Process Phase
Imagine these two sequences are executions of the a same process (the final product is the same even though one sequence is longer than the other one): CE
CE
CE
CE
CE
P. Viale, N. Benayadi, M. Le Goc, J. Pinaton
CE
Modeling Large Scale Manufacturing Process
Outline Introduction Extension of TOM4L Approach for Process Mining Application Conclusion and Future Work
Class of Equivalence Process Phase Potential Cycles Modeling a Large Scale Process
Extension of TOM4L Approach Process Phase
Imagine these two sequences are executions of the a same process (the final product is the same even though one sequence is longer than the other one): Corrective actions
CE
CE
CE
CE
CE
P. Viale, N. Benayadi, M. Le Goc, J. Pinaton
CE
Main Process
Main Process
Modeling Large Scale Manufacturing Process
Outline Introduction Extension of TOM4L Approach for Process Mining Application Conclusion and Future Work
Class of Equivalence Process Phase Potential Cycles Modeling a Large Scale Process
Extension of TOM4L Approach Process Phase
We introduce the idea of Process Phase to identify when a repetition of a task changes the state of the manufactured object With use sequence alignment information for identifying Process Phases
P. Viale, N. Benayadi, M. Le Goc, J. Pinaton
Modeling Large Scale Manufacturing Process
Outline Introduction Extension of TOM4L Approach for Process Mining Application Conclusion and Future Work
Class of Equivalence Process Phase Potential Cycles Modeling a Large Scale Process
Extension of TOM4L Approach Process Phase
We use a GOOD Sequence Alignment for cutting sequences into Process Phases:
CE
CE
P. Viale, N. Benayadi, M. Le Goc, J. Pinaton
CE
CE
CE
Modeling Large Scale Manufacturing Process
Outline Introduction Extension of TOM4L Approach for Process Mining Application Conclusion and Future Work
Class of Equivalence Process Phase Potential Cycles Modeling a Large Scale Process
Extension of TOM4L Approach Process Phase
By GOOD we mean: that aligns similar treatments done in different executions of the process in a same column that aligns special treatments for correcting error with gaps (’-’) Corrective actions CE
CE
P. Viale, N. Benayadi, M. Le Goc, J. Pinaton
CE
CE
CE
Modeling Large Scale Manufacturing Process
Outline Introduction Extension of TOM4L Approach for Process Mining Application Conclusion and Future Work
Class of Equivalence Process Phase Potential Cycles Modeling a Large Scale Process
Extension of TOM4L Approach Process Phase
By GOOD we mean: that aligns similar treatments done in different executions of the process in a same column that aligns special treatments for correcting error with gaps (’-’) Process Phase i CE
CE
P. Viale, N. Benayadi, M. Le Goc, J. Pinaton
CE
Process Phase i + 1 CE
CE
Modeling Large Scale Manufacturing Process
Outline Introduction Extension of TOM4L Approach for Process Mining Application Conclusion and Future Work
Class of Equivalence Process Phase Potential Cycles Modeling a Large Scale Process
Extension of TOM4L Approach Process Phase
One of the first issue that arise when comparing sequences concerns the estimation of substitution costs These substitution costs provide useful information that leads the algorithms to align or not the residues of the sequences considered The scores for aligning the different characters in the alphabet Σ are obtained from a matrix S = [sx ,y ]x ∈Σ,y ∈Σ , called similarity matrix. The value sx ,y represents the similarity between the elements of the pair (x , y ), x ∈ Σ, y ∈ Σ. Working with a wrong sequence alignment will probably conduce to errors when cutting sequences in Process Phases P. Viale, N. Benayadi, M. Le Goc, J. Pinaton
Modeling Large Scale Manufacturing Process
Outline Introduction Extension of TOM4L Approach for Process Mining Application Conclusion and Future Work
Class of Equivalence Process Phase Potential Cycles Modeling a Large Scale Process
Extension of TOM4L Approach Potential Cycles
The notion Potential Cycle characterizes situations where data does not provide an order between event classes CD
CA
CB
CE
CC
C A ,C B ,C D ,C C ,C E C A ,C B ,C C ,C D ,C E C A ,C B ,C C ,C D ,C E P. Viale, N. Benayadi, M. Le Goc, J. Pinaton
Modeling Large Scale Manufacturing Process
Outline Introduction Extension of TOM4L Approach for Process Mining Application Conclusion and Future Work
Class of Equivalence Process Phase Potential Cycles Modeling a Large Scale Process
Extension of TOM4L Approach Potential Cycles
The notion Potential Cycle characterizes situations where data does not provide an order between event classes CD
CA
CB
CE
CC
C A ,C B ,C D ,C C ,C E C A ,C B ,C C ,C D ,C E C A ,C B ,C C ,C D ,C E P. Viale, N. Benayadi, M. Le Goc, J. Pinaton
Modeling Large Scale Manufacturing Process
Outline Introduction Extension of TOM4L Approach for Process Mining Application Conclusion and Future Work
Class of Equivalence Process Phase Potential Cycles Modeling a Large Scale Process
Extension of TOM4L Approach Potential Cycles
So, we replace Potential Cycles with All Possible Paths between the event classes concerned in the cycle CD
CA
CB
CE
CC
C A ,C B ,C D ,C C ,C E C A ,C B ,C C ,C D ,C E C A ,C B ,C C ,C D ,C E P. Viale, N. Benayadi, M. Le Goc, J. Pinaton
Modeling Large Scale Manufacturing Process
Outline Introduction Extension of TOM4L Approach for Process Mining Application Conclusion and Future Work
Class of Equivalence Process Phase Potential Cycles Modeling a Large Scale Process
Extension of TOM4L Approach Potential Cycles
So, we replace Potential Cycles with All Possible Paths between the event classes concerned in the cycle CD
CA
CC
CB
CE
CC
CD
C A ,C B ,C D ,C C ,C E C A ,C B ,C C ,C D ,C E C A ,C B ,C C ,C D ,C E P. Viale, N. Benayadi, M. Le Goc, J. Pinaton
Modeling Large Scale Manufacturing Process
Outline Introduction Extension of TOM4L Approach for Process Mining Application Conclusion and Future Work
Class of Equivalence Process Phase Potential Cycles Modeling a Large Scale Process
Extension of TOM4L Approach Potential Cycles
So, we replace Potential Cycles with All Possible Paths between the event classes concerned in the cycle CD
CA
CC
CB
CE
CC
CD
C A ,C B ,C D ,C C ,C E C A ,C B ,C C ,C D ,C E C A ,C B ,C C ,C D ,C E P. Viale, N. Benayadi, M. Le Goc, J. Pinaton
Modeling Large Scale Manufacturing Process
Outline Introduction Extension of TOM4L Approach for Process Mining Application Conclusion and Future Work
Class of Equivalence Process Phase Potential Cycles Modeling a Large Scale Process
Extension of TOM4L Approach Modeling a Large Scale Process
Algorithm for modeling a large scale manufacturing process: 1 Find all equivalent classes in the sequences Ω considered and rewrite the sequences. 2 Calculate sequence alignment over the sequences Ω considered and rename classes that are aligned with gaps or different equivalent classes 3 Cut the sequences of Ω when there is a repetition of an equivalent class and produce the sets Ωk of subsequences ωki (Process Phases) 4 ∀Ω do k Build a process model Mk of the phase k with the BJT4G Algorithm (Potential Cycles replaced). 5
Concatenate all Mk for obtaining a model M of the hole process P. Viale, N. Benayadi, M. Le Goc, J. Pinaton
Modeling Large Scale Manufacturing Process
Outline Introduction Extension of TOM4L Approach for Process Mining Application Conclusion and Future Work
Modeling STMicroelectronics’ Manufacturing Processes
Application Modeling STMicroelectronics’ Manufacturing Processes
STMicroelectronics’ manufacturing processes can be seen (lowest level of abstraction) as a sequence of tasks called ’recipes’ that are executed on different equipments Corrective actions paths are called ’Rework Routes’ (STMicroelectronics’ Vocabulary) Rework Route Rework Route
Rework Route
...
P. Viale, N. Benayadi, M. Le Goc, J. Pinaton
Main Process
Modeling Large Scale Manufacturing Process
Outline Introduction Extension of TOM4L Approach for Process Mining Application Conclusion and Future Work
Modeling STMicroelectronics’ Manufacturing Processes
Application Modeling STMicroelectronics’ Manufacturing Processes
For validating approach, a set Ω containing 5 sequences ωi , i = {1, . . . , 5}, has been extracted from STMicroelectronics’ databases. Only the 200 first executed recipes were used in the example. The Algorithm has been applied at the equipment level so that a process model represents a manufacturing process as a sequence of equipments
P. Viale, N. Benayadi, M. Le Goc, J. Pinaton
Modeling Large Scale Manufacturing Process
Outline Introduction Extension of TOM4L Approach for Process Mining Application Conclusion and Future Work
Modeling STMicroelectronics’ Manufacturing Processes
Application Modeling STMicroelectronics’ Manufacturing Processes
In these sequences an event class is defined with a singleton C i = {(φi , i)} where the constant i is a natural number in the interval [1000, . . . , 1126]. Each of these event classes represent a particular equipment in STMicroelectronics’ plant. We will illustrate the application of the approach proposed in this paper showing how it works over two subsequences of sequences ω1 and ω2 used for the example construction.
P. Viale, N. Benayadi, M. Le Goc, J. Pinaton
Modeling Large Scale Manufacturing Process
Outline Introduction Extension of TOM4L Approach for Process Mining Application Conclusion and Future Work
Modeling STMicroelectronics’ Manufacturing Processes
Application Modeling STMicroelectronics’ Manufacturing Processes
w1 1010
1030
1040
1050
1061
1070
1041
1011
1032
1081
1052
1010
1020
1031
1051
1060
1071
1012
1033
1040
1080
1052
w2
P. Viale, N. Benayadi, M. Le Goc, J. Pinaton
Modeling Large Scale Manufacturing Process
Outline Introduction Extension of TOM4L Approach for Process Mining Application Conclusion and Future Work
Modeling STMicroelectronics’ Manufacturing Processes
Application Modeling STMicroelectronics’ Manufacturing Processes
Algorithm for modeling a large scale manufacturing process: 1
Find all equivalent classes in the sequences Ω considered and rewrite the sequences.
P. Viale, N. Benayadi, M. Le Goc, J. Pinaton
Modeling Large Scale Manufacturing Process
Outline Introduction Extension of TOM4L Approach for Process Mining Application Conclusion and Future Work
Modeling STMicroelectronics’ Manufacturing Processes
Application Modeling STMicroelectronics’ Manufacturing Processes
Consider that for ω1 and ω2 we found the following equivalent classes: {C 1031 , C 1032 , C 1033 } ⊆ C 6008 {C 1010 , C 1011 , C 1012 } ⊆ C 6009 {C 1050 , C 1051 , C 1052 } ⊆ C 6031 {C 1040 , C 1041 } ⊆ C 6040 {C 1020 } ⊆ C 6042 {C 1060 , C 1061 } ⊆ C 6046 {C 1080 , C 1081 } ⊆ C 6056 {C 1070 , C 1071 } ⊆ C 6065 P. Viale, N. Benayadi, M. Le Goc, J. Pinaton
Modeling Large Scale Manufacturing Process
Outline Introduction Extension of TOM4L Approach for Process Mining Application Conclusion and Future Work
Modeling STMicroelectronics’ Manufacturing Processes
Application Modeling STMicroelectronics’ Manufacturing Processes
Rewriting sequences: w1 1010
1030
1040
1050
1061
1070
1041
1011
1032
1081
1052
1010
1020
1031
1051
1060
1071
1012
1033
1040
1080
1052
w2
P. Viale, N. Benayadi, M. Le Goc, J. Pinaton
Modeling Large Scale Manufacturing Process
Outline Introduction Extension of TOM4L Approach for Process Mining Application Conclusion and Future Work
Modeling STMicroelectronics’ Manufacturing Processes
Application Modeling STMicroelectronics’ Manufacturing Processes
Rewriting sequences: w1 6009
6008
6040
6031
6046
6065
6040
6009
6008
6056
6031
6009
6042
6008
6031
6046
6065
6009
6008
6040
6056
6031
w2
P. Viale, N. Benayadi, M. Le Goc, J. Pinaton
Modeling Large Scale Manufacturing Process
Outline Introduction Extension of TOM4L Approach for Process Mining Application Conclusion and Future Work
Modeling STMicroelectronics’ Manufacturing Processes
Application Modeling STMicroelectronics’ Manufacturing Processes
Algorithm for modeling a large scale manufacturing process: 1
Find all equivalent classes in the sequences Ω considered and rewrite the sequences.
2
Calculate sequence alignment over the sequences Ω considered and rename classes that are aligned with gaps or different equivalent classes
P. Viale, N. Benayadi, M. Le Goc, J. Pinaton
Modeling Large Scale Manufacturing Process
Outline Introduction Extension of TOM4L Approach for Process Mining Application Conclusion and Future Work
Modeling STMicroelectronics’ Manufacturing Processes
Application Modeling STMicroelectronics’ Manufacturing Processes
Different Possible Similarity Matrices between equivalent classes: S1 = S2 =
− 6008 6009 6031 6040 6042 6046 6056 6065 − 6008 6009 6031 6040 6042 6046 6056 6065
6008 1 0 0 0 0 0 0 0 6008 1 −1 −1 −1 −1 −1 −1 −1
6009 0 1 0 0 0 0 0 0 6009 −1 1 −1 −1 −1 −1 −1 −1
6031 0 0 1 0 0 0 0 0 6031 −1 −1 1 −1 −1 −1 −1 −1
P. Viale, N. Benayadi, M. Le Goc, J. Pinaton
6040 0 0 0 1 0 0 0 0 6040 −1 −1 −1 1 −1 −1 −1 −1
6042 0 0 0 0 1 0 0 0 6042 −1 −1 −1 −1 1 −1 −1 −1
6046 0 0 0 0 0 1 0 0 6046 −1 −1 −1 −1 −1 1 −1 −1
6056 0 0 0 0 0 0 1 0 6056 −1 −1 −1 −1 −1 −1 1 −1
6065 0 0 0 0 0 0 0 1 6065 −1 −1 −1 −1 −1 −1 −1 1
Modeling Large Scale Manufacturing Process
Outline Introduction Extension of TOM4L Approach for Process Mining Application Conclusion and Future Work
Modeling STMicroelectronics’ Manufacturing Processes
Application Modeling STMicroelectronics’ Manufacturing Processes
Alignment between ω1 and ω2 using similarity matrix S1 : w1 6009
6008
6040
6031
6046
6065
6040
6009
6008
6056
6031
6009
6042
6008
6031
6046
6065
6009
6008
6040
6056
6031
w2
P. Viale, N. Benayadi, M. Le Goc, J. Pinaton
Modeling Large Scale Manufacturing Process
Outline Introduction Extension of TOM4L Approach for Process Mining Application Conclusion and Future Work
Modeling STMicroelectronics’ Manufacturing Processes
Application Modeling STMicroelectronics’ Manufacturing Processes
Alignment between ω1 and ω2 using similarity matrix S2 : Better Alignment!
w1 6009
6009
6008
6042
6008
6040
6031
6046
6065
6031
6046
6065
6040
6009
6008
6009
6008
6040
w2
P. Viale, N. Benayadi, M. Le Goc, J. Pinaton
Modeling Large Scale Manufacturing Process
6056
6031
6056
6031
Outline Introduction Extension of TOM4L Approach for Process Mining Application Conclusion and Future Work
Modeling STMicroelectronics’ Manufacturing Processes
Application Modeling STMicroelectronics’ Manufacturing Processes
Alignment between ω1 and ω2 using similarity matrix S2 : Better Alignment!
w1 6009
6009
6008
6042
6008
6040
6031
6046
6065
6031
6046
6065
6040
6009
6008
6009
6008
6040
w2
P. Viale, N. Benayadi, M. Le Goc, J. Pinaton
Modeling Large Scale Manufacturing Process
6056
6031
6056
6031
Outline Introduction Extension of TOM4L Approach for Process Mining Application Conclusion and Future Work
Modeling STMicroelectronics’ Manufacturing Processes
Application Modeling STMicroelectronics’ Manufacturing Processes
Alignment between ω1 and ω2 using similarity matrix S2 : Better Alignment!
w1 6009
6009
6008
6042
6008
6040
6031
6046
6065
6031
6046
6065
6040
6009
6008
6009
6008
6040
w2
P. Viale, N. Benayadi, M. Le Goc, J. Pinaton
Modeling Large Scale Manufacturing Process
6056
6031
6056
6031
Outline Introduction Extension of TOM4L Approach for Process Mining Application Conclusion and Future Work
Modeling STMicroelectronics’ Manufacturing Processes
Application Modeling STMicroelectronics’ Manufacturing Processes
Alignment between ω1 and ω2 using similarity matrix S2 : Better Alignment!
w1 6009
6009
6008
6067 6042
6008
6068 6040
6031
6046
6065
6031
6046
6065
6069 6040
6009
6008
6009
6008
6070 6040
w2
P. Viale, N. Benayadi, M. Le Goc, J. Pinaton
Modeling Large Scale Manufacturing Process
6056
6031
6056
6031
Outline Introduction Extension of TOM4L Approach for Process Mining Application Conclusion and Future Work
Modeling STMicroelectronics’ Manufacturing Processes
Application Modeling STMicroelectronics’ Manufacturing Processes
Alignment between ω1 and ω2 using similarity matrix S2 : Better Alignment!
w1 6009
6009
6008
6067 6042
6008
6068 6040
6031
6046
6065
6031
6046
6065
6069 6040
6009
6008
6009
6008
6070 6040
w2
P. Viale, N. Benayadi, M. Le Goc, J. Pinaton
Modeling Large Scale Manufacturing Process
6056
6031
6056
6031
Outline Introduction Extension of TOM4L Approach for Process Mining Application Conclusion and Future Work
Modeling STMicroelectronics’ Manufacturing Processes
Application Modeling STMicroelectronics’ Manufacturing Processes
Algorithm for modeling a large scale manufacturing process: 1
Find all equivalent classes in the sequences Ω considered and rewrite the sequences.
2
Calculate sequence alignment over the sequences Ω considered and rename classes that are aligned with gaps or different equivalent classes
3
Cut the sequences of Ω when there is a repetition of an equivalent class and produce the sets Ωk of subsequences ωki (Process Phases)
P. Viale, N. Benayadi, M. Le Goc, J. Pinaton
Modeling Large Scale Manufacturing Process
Outline Introduction Extension of TOM4L Approach for Process Mining Application Conclusion and Future Work
Modeling STMicroelectronics’ Manufacturing Processes
Application Modeling STMicroelectronics’ Manufacturing Processes
w1 6009
6009
6008
6067
6008
6068
6031
6046
6065
6031
6046
6065
6069
6009
6008
6009
6008
6070
w2
P. Viale, N. Benayadi, M. Le Goc, J. Pinaton
Modeling Large Scale Manufacturing Process
6056
6031
6056
6031
Outline Introduction Extension of TOM4L Approach for Process Mining Application Conclusion and Future Work
Modeling STMicroelectronics’ Manufacturing Processes
Application Modeling STMicroelectronics’ Manufacturing Processes
w1 6009
6009
6008
6067
6008
6068
6031
6046
6065
6031
6046
6065
6069
6009
6008
6009
6008
6070
w2
P. Viale, N. Benayadi, M. Le Goc, J. Pinaton
Modeling Large Scale Manufacturing Process
6056
6031
6056
6031
Outline Introduction Extension of TOM4L Approach for Process Mining Application Conclusion and Future Work
Modeling STMicroelectronics’ Manufacturing Processes
Application Modeling STMicroelectronics’ Manufacturing Processes
w1 6009
6009
Process Phase i + 1
Process Phase i 6008
6067
6008
6068
6031
6046
6065
6031
6046
6065
6069
6009
6008
6009
6008
6070
w2
P. Viale, N. Benayadi, M. Le Goc, J. Pinaton
Modeling Large Scale Manufacturing Process
6056
6031
6056
6031
Outline Introduction Extension of TOM4L Approach for Process Mining Application Conclusion and Future Work
Modeling STMicroelectronics’ Manufacturing Processes
Application Modeling STMicroelectronics’ Manufacturing Processes
w1i
Process Phase i
0
6009
0
6009
6008
6067
6068
6008
6031
6046
6065
6031
6046
6065
6069
1 1
w2i w1i+1
Process Phase i + 1
0
6009
6008
0
6009
6008
6070
6056
6031
1
6056
6031
1
w2i+1 P. Viale, N. Benayadi, M. Le Goc, J. Pinaton
Modeling Large Scale Manufacturing Process
Outline Introduction Extension of TOM4L Approach for Process Mining Application Conclusion and Future Work
Modeling STMicroelectronics’ Manufacturing Processes
Application Modeling STMicroelectronics’ Manufacturing Processes
Algorithm for modeling a large scale manufacturing process: 1
Find all equivalent classes in the sequences Ω considered and rewrite the sequences.
2
Calculate sequence alignment over the sequences Ω considered and rename classes that are aligned with gaps or different equivalent classes
3
Cut the sequences of Ω when there is a repetition of an equivalent class and produce the sets Ωk of subsequences ωki (Process Phases) ∀Ωk do
4
Build a process model Mk of the phase k with the BJT4G Algorithm (Potential Cycles replaced) P. Viale, N. Benayadi, M. Le Goc, J. Pinaton
Modeling Large Scale Manufacturing Process
Outline Introduction Extension of TOM4L Approach for Process Mining Application Conclusion and Future Work
Modeling STMicroelectronics’ Manufacturing Processes
Application Modeling STMicroelectronics’ Manufacturing Processes
Model Process Phase i 0
6009
6008
6031
6067
6046
1
6065
6068
6069
Model Process Phase i + 1 0
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P. Viale, N. Benayadi, M. Le Goc, J. Pinaton
Modeling Large Scale Manufacturing Process
Outline Introduction Extension of TOM4L Approach for Process Mining Application Conclusion and Future Work
Modeling STMicroelectronics’ Manufacturing Processes
Application Modeling STMicroelectronics’ Manufacturing Processes
Algorithm for modeling a large scale manufacturing process: 1 Find all equivalent classes in the sequences Ω considered and rewrite the sequences. 2 Calculate sequence alignment over the sequences Ω considered and rename classes that are aligned with gaps or different equivalent classes 3 Cut the sequences of Ω when there is a repetition of an equivalent class and produce the sets Ωk of subsequences ωki (Process Phases) 4 ∀Ω do k Build a process model Mk of the phase k with the BJT4G Algorithm (Potential Cycles replaced) 5
Concatenate all Mk for obtaining a model M of the hole process P. Viale, N. Benayadi, M. Le Goc, J. Pinaton
Modeling Large Scale Manufacturing Process
Outline Introduction Extension of TOM4L Approach for Process Mining Application Conclusion and Future Work
Modeling STMicroelectronics’ Manufacturing Processes
Application Modeling STMicroelectronics’ Manufacturing Processes
Algorithm for modeling a large scale manufacturing process: 1 Find all equivalent classes in the sequences Ω considered and rewrite the sequences. 2 Calculate sequence alignment over the sequences Ω considered and rename classes that are aligned with gaps or different equivalent classes 3 Cut the sequences of Ω when there is a repetition of an equivalent class and produce the sets Ωk of subsequences ωki (Process Phases) 4 ∀Ω do k Build a process model Mk of the phase k with the BJT4G Algorithm (Potential Cycles replaced) 5
Concatenate all Mk for obtaining a model M of the hole process P. Viale, N. Benayadi, M. Le Goc, J. Pinaton
Modeling Large Scale Manufacturing Process
Outline Introduction Extension of TOM4L Approach for Process Mining Application Conclusion and Future Work
Conclusion Future Work
Conclusion The discrete event classes of equivalence are required for reducing the size of the models when treating large scale manufacturing processes Process phase concept is also important to identify the different states that the manufactured object goes through The importance of ’GOOD’ sequence alignment for identifying Process Phases has been shown in the applicative section First examples constructed using this algorithm (modeling STMicroelectronics’ (Rousset) manufacturing processes) has shown promising results
P. Viale, N. Benayadi, M. Le Goc, J. Pinaton
Modeling Large Scale Manufacturing Process
Outline Introduction Extension of TOM4L Approach for Process Mining Application Conclusion and Future Work
Conclusion Future Work
Future Work
Our future work consist in implementing an alignment algorithm capable of treating large volumes of data (at least 40 sequences of 1000 recipes long) Also, we would like to implement an algorithm for calculating similarity matrices deriving costs empirically.
P. Viale, N. Benayadi, M. Le Goc, J. Pinaton
Modeling Large Scale Manufacturing Process
Outline Introduction Extension of TOM4L Approach for Process Mining Application Conclusion and Future Work
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P. Viale, N. Benayadi, M. Le Goc, J. Pinaton
Modeling Large Scale Manufacturing Process
