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Description

The following case study illustrates a scenario, proposed by Donnafugata, related to the wine production. It involves a Wine Producer who wants to maximize his production in order to adapt it according to the monitored market needs. Other actors of the scenario are the Quality Manager, the Agronomist (i.e., an expert of a branch of agriculture which deals with field-crop production and soil management) and the Oenologist (i.e., an expert of wine and wine production). They have to observe the vineyard parameters and to react to critical conditions that may happen during the cultivation phase. Critical conditions may be represented by overcoming the threshold for some particular environmental parameter. The case study also shows the processes involving the harvesting of the grapes and the logistics to deliver the product to retailers.

Business Goals and Domain Assumptions

In this sections the Business Goals and the Domain Assumptions for the current case study will be reported.

Business Goals

Table BG1. Business Goal WINERY-S-BG1
Field Description
UniqueID WINERY-S-BG1
Short Name Observe Market Needs
Type Business Goals.
Description Starting from the domain information, the system shall provide a way to infer critical conditions from the analysis of market needs. It shall react in an automatic way to those critical conditions, both selecting predefined reactions and inferring reactions from a knowledge base. Standard reactions are provided in the scenarios and in the domain sections.
Rationale Maximize sales volume.
Involved Stakeholders Quality Manager
Conflicts None
Supporting Material
Priority of accomplishment Must have.


Table BG2. Business Goal WINERY-S-BG2
Field Description
UniqueID WINERY-S-BG2
Short Name Observe vineyard cultivation
Type Business Goals.
Description The system shall provide a way to infer critical conditions from observing vineyard parameters. It shall provide a way to react in an automatic way to those critical conditions, both from selecting predefined reactions and inferring reactions from a knowledge base. Notifications to the Quality Manager, Oenologist and Agronomist shall be included in such predefined reactions. Other standard reactions are provided in the scenarios and in the domain sections.
Rationale Maximize sales volume and wine quality.
Involved Stakeholders Quality Manager, Oenologist, Agronomist
Conflicts None
Supporting Material
Priority of accomplishment Must have.


Table BG3. Business Goal WINERY-S-BG3
Field Description
UniqueID WINERY-S-BG3
Short Name Observe maturation, fermentation and harvesting
Type Business Goals.
Description The infrastructure shall provide: a way to infer critical conditions from observing vineyard parameters; a way to react in an automatic way to those critical conditions, both from selecting predefined reactions and inferring reactions from a knowledge base. Notifications to the Quality Manager are included in such predefined reactions, especially if the critical conditions require manual interventions. Other standard reactions are provided in the description of the case study. Moreover, the Quality Manager shall be able to control quality parameters explicitly.
Rationale Maximize sales volume and wine quality. In particular, this business goal handles the management of the critical conditions during phases following cultivation.
Involved Stakeholders Quality Manager, Oenologist
Conflicts None
Supporting Material
Priority of accomplishment Must have.

Domain Assumptions

Table DA1. Assumption WINERY-S-DA1
Field Description
UniqueID WINERY-S-DA1
Short Name The system to be should be driven by a self-managing business process
Type Domain assumption
Description The overall business process must be designed such that it shall perform self-management, that is, it shall implement the so-called MAPE cycle, that adheres to the scenario related to this assumption. In the MAPE cycle, the execution of the business process is based on a paradigm that involves resource Monitoring, collected data Analysis, intervention Plan, and action Execution. In the case of the proposed scenario, monitoring comes from the physical infrastructure (see next assumption), and the remaining parts of the paradigm must be implemented by the self-managing business process, which permits to define intervention plans and action executions after a critical condition detection as required by the related scenario. In this approach, detection of market changes and reaction to these changes shall be implemented as a particular instance of the MAPE cycle within the autonomic infrastructure.
Rationale See Description.
Involved Stakeholders Quality Manager
Conflicts None
Supporting Material
Priority of accomplishment Should have.


Table DA2. Assumption WINERY-S-DA2
Field Description
UniqueID WINERY-S-DA2
Short Name Vineyard is equipped with a wireless sensor and actuator network.
Type Domain assumption
Description This assumption arises from the necessity of examining parameters of vineyards, which are spatially distributed among cultivation fields. This infrastructure can be seen at the business level from two possible points of view: by a process manager component of a workflow engine or from a query layer infrastructure that offers the ability of programming events generation to deploy directly into the sensor networks. Sensors are needed to observe quality attributes of grapes during the phases of the

production process.

Rationale A distribute Wireless Sensor Network (WSN) infrastructure shall be able to sense the environment of vineyards and collect data.
Involved Stakeholders Quality Manager, Agronomist
Conflicts None
Supporting Material
Priority of accomplishment Could have


Table DA3. Assumption WINERY-S-DA3
Field Description
UniqueID WINERY-S-DA3
Short Name Time between harvesting and processing should be limited
Type Domain assumption
Description This assumption is a very simple constraint on the business process, that requires that the time between harvesting and processing of the grapes must be limited, typically within one hour, or it must be related to specific requirements of a particular production.
Rationale Maximize the quality of the final product.
Involved Stakeholders Quality Manager
Conflicts None
Supporting Material
Priority of accomplishment Must have


Table DA4. Assumption WINERY-S-DA4
Field Description
UniqueID WINERY-S-DA4
Short Name Logistic is supported through a RFID system.
Type Domain assumption
Description This assumption constrains the design of the physical and logical infrastructure for the observing and querying of temperature during the distribution phase. Moreover each bottle has associated a RFID, each pallet has associated a RFID data logger. In this case, since it is necessary to track and record the temperature information of moving packages, RFIDs and data loggers are suggested to be used. Moreover, to provide an uniform method for querying in such a physical architecture, a query layer for pervasive infrastructure should be used, such as PERLA. Finally, this infrastructure should be interfaced with the self-managing business process, in order to use it as a source for reacting to possible critical events regarding distribution.
Rationale See Description.
Involved Stakeholders Delivery Company, Retailer
Conflicts None
Supporting Material
Priority of accomplishment Could have

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Scenarios

The figure shows the general use-case diagram for the Vineyard case study.

UC.jpeg


Table S1: Scenario WINERY-S-CH-1
Field Description
UniqueID WINERY-S-CH-1
Short Name Cultivation Handling
Related To WINERY-S-BG1, WINERY-S-BG2, WINERY-S-DA1, WINERY-SDA2
Involved Actors The actors involved in the cultivation handling scenario are the agronomist, the oenologist, the quality manager and the Wine Grower. Moreover, the market has some role on determining which vineyard should be cultivated.
Detailed Operational Description Cultivation handling is mainly performed by the agronomist, the oenologist and by the Wine Grower; it is supposed that they handle N vineyards of a wine producer (winery). For each vineyard, the handling process implies the analysis of functional parameters such as temperature, humidity, light, wind speed, etc. in specific months of the year. The kind of vineyards to be cultivated are determined by information coming from the market, in the sense that using statistical data about sales of previous years, the enterprise infers which vineyards are more likely to be cultivated in order to produce the kind of wines that will maximize sales. The agronomist and oenologist determine the vineyard quality by analyzing gathered information. It may happen that those actors could detect critical conditions on which some recovery actions should be performed in order to react and prevent damages for the wine production. Critical conditions can involve some events on the environment (such as frost destroying the vineyard), or some other events involving the measurement of the quality versus its estimate coming from market information. The identification of the recovery actions is performed by the quality manager together with the oenologist and the agronomist. Actions include notifications and complex processes to be performed by different actors.
Problems and Challenges The main problems arising with the described complex scenario involve:
  • handling the complex process of vineyard cultivation management;
  • identification of recovering actions;
  • automatization of observing vineyard parameters, detection of critical conditions and performing of recovery actions.
  • provide an automated way to infer an estimate of market needs;
Additional Material The following Activity Diagram shows the sequence of the activities to be done in the current scenario.CH.jpeg



Table S2: Scenario WINERY-S-CH-2
Field Description
UniqueID WINERY-S-CH-2
Short Name Managing the Market Needs
Related To WINERY-S-BG1, WINERY-S-BG2
Involved Actors Market and Wine Producer
Detailed Operational Description Inputs derived from market needs must be properly managed. In this scenario, it must be possible for the information system to get forecasts for the current year, in terms of specific sales volume, together with wine kind and its quality. Thus, the information system of the enterprise should be able to infer the kind of grapes and consequently the vineyard to be cultivated. Moreover, from the observing vineyard parameters activity, it should be possible to estimate the quality of wine based on the health status of the vineyard (based also on the information gathered during all the production phases). During the management process, it must be possible to detect some critical conditions regarding the estimated wine quality. One of those condition is the following: ”the estimated Qs from the observing activity seems to be too much different from the quality Q desired from customers”; other conditions are more low level and they are related to specific vineyard conditions. A possible response action to these conditions is buying from other producers an amount of grapes automatically suggested by the observing system.
Problems and Challenges The main problems arising with the described complex scenario involve:
  • proper detection (inference) of market needs;
  • proper identification of recovering and response actions.
Additional Material The following Activity Diagram shows the sequence of the activities to be done in the current scenario.Sub-4.jpeg



Table S3: Scenario WINERY-S-HFM
Field Description
UniqueID WINERY-S-HFM
Short Name Harvesting and Fermentation
Related To WINERY-S-DA1, WINERY-S-DA2, WINERY-S-BG3
Involved Actors Quality Manager and Oenologist
Detailed Operational Description In those three phases, the quality manager should be helped to control quality attributes to keep the wine production quality at the required level.

The controlled phases are the following:

  • Harvesting; is a critical part of the wine production process. Usually, it is necessary to:
    • Minimize the interval between harvesting and grapes processing;
    • Evaluate climatic conditions for harvesting (depending on the particular kind of grapes or production, they may require specific climatic conditions);
  • Fermentation:
    • Chemical analysis (both “in loco” and in the lab) to monitor quality and avoid critical events, such as high concentration of acetic acid or presence of dangerous bacteria; those events must be properly communicated so that they can be properly managed by manual intervention;
    • acidity, humidity and temperature must be recorded in each cellar to monitor the quality of the produced wine.
  • In any transportation sub-phase, humidity and temperature must be observed.
Problems and Challenges The main problems arising with the described complex scenario involve:
  • provide a distributed and secure infrastructure for observing critical parameters, both during fermentation and harvesting;
  • monitor critical parameters during any transportation phase;
  • minimize the time between harvesting and the grapes processing.


Additional Material The following Activity Diagram shows the sequence of the activities to be done in the current scenario.HFM.jpeg



Table S4: Scenario WINERY-S-DS
Field Description
UniqueID WINERY-S-DS
Short Name Distribution and Sale
Related To WINERY-S-BG3, WINERY-S-DA1, WINERY-S-DA4
Involved Actors Quality Manager, Wine Producer, Delivery Company and Retailer
Detailed Operational Description During the sales phase the Wine Producer interact with the Retailer to stipulate contracts. The orders will be delivered by the Delivery Company. During the sale phase, the quality manager is interested in the returns in order to compare them with the conditions of the product during all the life-cycle models. During the distribution phase, the quality manager must be able to assure that, starting from monitored values, the temperature variation meets some strict requirements (i.e., no wide fluctuations and it must be kept within a specific range).
Problems and Challenges The main problems arising with the described complex scenario involve:
  • provide a distributed and secure infrastructure for observing critical

parameters during distribution;

  • provide an infrastructure to track market information and predict

changes in the market in a narrow time scale.


Additional Material DistributionAndSales.jpeg


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