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Commit 59731cf5 authored by Pamela Dyer's avatar Pamela Dyer
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......@@ -21,74 +21,8 @@ agile production / building of alternative supply chains.
Specifically in this model, the focus is on the delivered
quality of 5,000 medical face shields (a Customer placed
the order using the APP). The narrative for this baseline
use case is as follows:
Precondition: A Customer has an urgent need for 5,000
medical face shields.
1. Customer logs into the APP linkage platform.
2. APP authenticates valid customer credentials and prompts the Customer for the need.
3. Customer inputs a need for 5,000 units of a medical face shield with desired
attributes.
4. APP identifies the individual components of the needed item.
5. APP determines which Sector Resources to search for equivalent components (prepares
component search parameters).
6. APP searches Sector Resources for available component matches and their attributes
(e.g., availability, timeliness, cost, reliability, quality, quantity).
7. APP assembles combinations of available components having intersecting
attributes (find component matches).
8. The APP constructs a list of valid supply chain elements.
8a. If the supply chain for the order is complete, the APP displays the order options to the
Customer along with soonest delivery time, total cost, and component attributes for
each participant in the chain (e.g., participant reputation, material specifications,
product dimensions, suitability for certification).
8b. Otherwise if one or more components is unavailable, the APP reprocesses the order with
a new search for equivalent alternatives to the missing component(s) (back to step 5).
9a. If the supply chain is complete, the Customer receives the order options from the APP
and filters, sorts, and inspects the presented solutions, selects a solution, and places
the order.
9a-1. The order is delivered to the Customer and meets their expectations.(Favorable
Outcome)
9a-2. The order is delivered to the Customer and does not meet their expectations.
(Unfavorable Outcome)
9a-3. The order is not delivered to the Customer (Unfavorable Outcome).
9b. If no alternative supply chain can be found, the Customer is notified by the APP that the
order cannot be completed at this time. (Unfavorable Outcome)
Assumptions/Abstractions:
The "Data for supply chain" event that is included in the APP and the Data Services/
Resources root represents asynchronous and continuous data for support to the
alternative supply chain construction. The individual interactions involved here
are another level of refinement reserved for a separate MP model that can be elaborated
separately from this model which focuses on the Customer-APP interactions.
Known ways to get to an unfavorable outcome:
- Customer asks for a disproportionately large amount of product and the system is strained
for other users
- Allow for aggregation
Questions:
- Does the APP prioritize orders?
- Can a customer get orders with "some assembly required" or does it come assembled from
some service provider?
Postcondition: The Customer receives 5,000 face shields (not shown in the model yet).
Running this model at Scope 1 generates 4 event traces,
described as follows:
the order using the APP). Running this model at Scope 1
generates four event traces, described as follows:
Trace 1: The order is delivered to the Customer and
meets their expectations (Favorable Outcome).
Trace 2: The order is delivered to the Customer and
......@@ -115,15 +49,15 @@ SAY statement; trace annotation; event sharing; table;
behavior, unexpected; behavior, emergent;
behavior, agile production platform
Instructions: Run for Scope 1. Reviewers of this model are
Instructions: Run for Scope 1. Reviewers of this model are
invited to provide feedback for better-named events, other
events that may occur normally or as a disruption to the
sequence, missing or incorrect interactions, and the
partitioning of the high level APP functions for architectural
cohesion. Lower-level (implementation) activities have been
deliberately omitted for now in order to reach consensus on
intended use at the highest level of abstraction.
partitioning of the high level APP functions for
architectural cohesion. Lower-level (implementation)
activities have been deliberately omitted for now in order
to reach consensus on intended use at the highest level
of abstraction.
Scope 1: 4 traces in less than 1 sec.
==========================================================*/
......
......@@ -24,7 +24,7 @@ capacity even though the APP pooled more suppliers at all
levels of production, so the order was not fulfilled (an
Unfavorable Outcome). (This involved imagining an event
change under the Customer from receive to did not receive
product). An example of Unexpected Emergent Behavior
product). An example of Unexpected Emergent Behavior
coming out of this model is shown in trace 36: a
nonconforming material still making its way to the customer,
either through a miscommunication or lack of inspection
......
......@@ -9,18 +9,18 @@ governance framework.
Description: Models the data flow from sensors all the way
to the human analyst at a tactical location incorporating
a data governance framework. The AIS_Sensor represents an
a data governance framework. The AIS_Sensor represents an
example AIS GPS SENSOR; the Aggregation_Service represents
a local AIS Aggregator like a Radar system or local AIS
Broadcast; the Global_Distribution_Mechanism receives data
from multiple aggregation services, coalates the data, and
rebroadcasts the data globally. Within the
rebroadcasts the data globally. Within the
Global_Distribution_Mechanism, Source A represents raw AIS
tracks that have not been modified in any way prior to
dissemination; Source B represents raw AIS tracks grouped
into geographic areas for limited broadcast; Source C
represents custom filtering and combining of AIS tracks
based on unique fields. The Data Governance Framework
based on unique fields. The Data Governance Framework
applies an evaluation rubric to data sources and only allows
sources that are uncorrupted to be transmitted to the
correlator. The Data_Governance_Framework receives sources,
......@@ -39,7 +39,7 @@ Watson, Frank. "Design Methodologies for 21st Century
Watson, Frank. "Model of Correlation and Fusion Process
Ungoverned." 20 August 2021. In "Design Methodologies
for 21st Century Battlefield Object Correlation and
Fusion." NPS Master's Thesis, Monterey, CA: September
Fusion." NPS Master's Thesis, Monterey, CA: September
2021.
Example 49. Histogram showing number of traces with
......
......@@ -30,8 +30,8 @@ demonstrate calculating individual and total risk scores.
Description: This model demonstrates performing detailed
risk analysis on a supply chain potentially affected by
two cyber threats. This is made possible by combining two
MP models that each contained one threat: a cyber attack on
the barge, and a cyber attack on the Colonial Pipeline.
MP models that each contained one threat: a cyber attack
on the barge, and a cyber attack on the Colonial Pipeline.
All three of these models can be found in (Palmieri 2021).
This model first takes advantage of separate COORDINATE
......
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