| dc.description.abstract | The purpose of this thesis is to uncover and demonstrate how decision support systems can support centralised production planning across multiple whitefish processing facilities. To that end, a prototype of a graphical user interface for a decision support system has been developed along with a concept proposal for a complete system, both of which are presented in this thesis. The proposed system combines information which today is scattered between different systems and websites such as vessel catches, vessel quotas, recent fish landings, inventory holdings, sales contracts and more. The system is also a production planning tool which displays an overview of production plans for several processing facilities with the option to manually make changes to the plans. For the automatic generation of production plans, the proposed system has a production optimisation model and a raw materials prediction model. These models are described and discussed, but not in depth, as they are not the main focus of the thesis. The system is explained through textual descriptions, screenshots of the prototype and a conceptual software architecture.
The motivation for this thesis is the financial struggles of Norwegian whitefish processors. They are faced with many challenges such as the rapid perishability of fresh fish, supply uncertainty and demand uncertainty, seasonality, legal restrictions and more. The case study in this thesis revealed that there is a need for transparent, timely and readily available information to support production decisions.
The thesis includes a literature review on the topics of production planning, modelling approaches and optimisation models for whitefish processing and production networks, decision support systems and design. The production planning research focuses on hierarchical planning in production networks. Findings from the literature review are summarised in a conceptual framework. The case study investigates a Norwegian whitefish processing company, and consisted of a two-day company visit, a meeting with company representatives and content analysis of documents and websites. The most important findings from the case study are:
Transparency of raw materials and related information is the most needed decision support for centralised production planning
There is a need for decision support and availability of pertinent information in other business units
The conclusion argues that the purpose has been fulfilled by tackling the main challenges identified in the case study, but that there are likely more ways in which decision support systems can support production planning in whitefish processing networks which were not uncovered. | en |
