Case Study -Q46

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Background
 
The dairy industry operates in a difficult environment in Australia. Milk producers have come under considerable pressure by major supermarket chains in recent times. As a result, profit margins have been shrinking and farmers are looking to increase efficiency and productivity of their operations. In particular, managing production risk has been identified as one of the opportunities [1].
 
Precision Livestock Farming (PLF) aims to optimise the contribution of each individual animal by using advanced technologies [2,5]. Each animal is equipped with sensors, which continuously monitor the animal’s health and performance. Data analysis methods and decision support systems are used to adjust handling and feeding of each individual animal [3]. In the context of cattle farming, advanced sensor technology attached to cows’ ears can provide a detailed assessment about each cow’s health [4]. Such advanced health management technologies have the potential to reduce production risk, optimise quality and quantity, and scale the operations to serve the large emerging international markets in Asia.
 

ArchiFarm Case Study Description
 
ArchiFarm, a fictitious dairy producer, is a large dairy producer who operates three production sites. The main site in rural Victoria hosts ~2500 cows, and two smaller ones in NSW have ~200 cows each. Each site has a number of facilities, including an office building, the main shed where all the cows are housed, fed, and milked, and various storage and maintenance buildings.
 
ArchiFarm’s margins have been shrinking due to price pressure exercised by distributors and retailers. As a result, management has been seeking to minimise its production cost by improving the efficiency of its operations and leverage economies of scale when acquiring supplies.
 
The company implements standard governance structures, with the board including the CxO roles at the very top. The company’s logistic operations and client liaison are handled by the Kees Lokhorst (2012)company’s head office located in Sydney. Each production site is managed by a Site Manager who has responsibility for overseeing and directing the operations of the site. The Site Manager periodically reports production and other operational data to the head office who uses this data for planning purposes.
 
The Site Manager is supported by employees and farm workers. Each site maintains an administration office that performs HR and site management duties and organises contractors for maintenance works. The largest production site maintains a separate maintenance unit, whereas the smaller sites outsource maintenance to contractors.
 
ArchiFarm has contracts with a number of distributors, who collect and ship the milk in refrigerated containers by truck for further processing and wholesale. The collection schedule is pre-specified in the contract, and ArchiFarm is liable to pay compensation of the agreed quantity of fresh milk is unavailable or if the product fails to pass quality control procedures. For quality control purposes, the milk produced by sick cows is kept separate from the product obtained from healthy cows. ArchiFarm anticipates that PLF technologies will help detect and prevent significant health issues much earlier and reduce contamination of milk that may occur if a sick cow is identified too late.
 
ArchiFarm has agreements with a number of local animal feed producers to supply each production site with animal feed. Each site receives a fixed quantity of animal feed at regular intervals. This simple supply model has been sufficient as with the current feeding approach the feed quantities dispensed to each cow vary little.
ArchiFarm has already invested in automation technologies at its main production site, including automatic feeding stations that dispense a custom quantity of animal feed to each individual cow, and robotic milking stations that track the yield of each individual animal and adjust milking times for each cow (under- and over-milking of animals can have serious health consequences).
 
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The video in reference [6] shows a similar system. The smaller production sites do not have automated feeding lots and instead rely on farm workers dispense feed to each individual animal using tractors. Milking is performed using an older version of an automated milking system which can record the quantity of milk obtained from each cow. However, in contrast to the fully automated robot installed at the main site, the milking system must be moved from cow-to-cow by farm workers.
 
The quantity of milk produced by each animal is exported from the information system that controls the milking stations and analysed using a custom-built reporting software tool. The analysis results are used by farm staff to adjust feed quantities for individual animals and organise health assessments by veterinarians. Currently, emerging health issues are predominantly dealt-with at each individual site.
 
The assessment of each animal’s health is currently done predominantly by manual inspection and problems are usually discovered only once any health issues have advanced to the point where the animal’s yield or weight has been affected significantly. Records of health issues and remedial actions are kept in each animal’s health record. The health record is an informal text document stored on a file system hosted on a file server at each production site. If problems are detected, the cow’s feed mix and feed quantity are adjusted, and drugs may be added. This can be done via the control screen attached to the feeding control station at each production site.
 
ArchiFarm has learned about PLF technologies for health monitoring and wishes to implement data-driven health monitoring among all its production sites. Specifically, the company wishes to adopt sensors attached to cows’ ears [4] for PLF health management. This will require the company to construct and maintain an animal-specific health prediction model by automatically and continuously capturing the sensor readings from cows’ ears and integrate that with the animal’s milk production data and health information. The company intends to apply data mining and predictive analytics algorithms to anticipate potential problems well before serious illnesses occur. Learnings from one site should be immediately translated to other production sites in order to prevent the spread of illness.
 
Assessments
 
In this case study, you will document baseline and target architectures, conduct gap analysis, and develop a transition roadmap for ArchiFarm, who wishes to adopt sensors attached to cow’s ears [4] for PLF health management.
You will be analysing and modelling the current state (baseline) of the enterprise architecture of ArchiFarm, define the target architecture that includes the PLF capability and systems, and create an appropriate roadmap for the transition from baseline to future architecture.
 
These activities will be spread among the three assignments.

 
Assignment 1 will be concerned with the business and motivation aspects of the current enterprise; Assignment 2 will extend that with information and application architecture; and Assignment 3 will define the target architecture, conduct a gap analysis and define a transition roadmap.
 
To complete the assignments, you may need to research the dairy industry and farming practices and systems to get a better understanding of stakeholders, the business context, and business functions and processes and supporting information systems. Background information about dairy farming is available via the following resources. You may need to find and research further resources as needed.
 
You will likely need to make assumptions about ArchiFarm, its operations, and technologies. You are required to explicitly state the assumptions you have made in each assignment.
 
Product Code-Case Study -Q46
 
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