Fraunhofer Chalmers Research Centre for Industrial Mathematics
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Skiftöverlämning i sjukvården - En undersökning om effektiva möten och effektiv kommunikation
No full textDen svenska sjukvården står inför ett förändringsbehov för att kunna möta de framtida behov som beräknas uppstå. Tidigare studier utförda på Sahlgrenska universitetssjukhuset visar på brister i standardiserade arbetssätt vilket leder till minskad kvalité och effektivitet i arbetet.
Denna rapport syftar till att undersöka hur informationsöverlämningen i dagsläget sker mellan olika arbetslag på Sahlgrenska universitetssjukhuset genom att analysera olika parametrar för effektiva möten och effektiv kommunikation. Utöver detta har även en rekommendation med förbättringsmöjligheter tagits fram för att bemöta de problemområden som upptäckts.
Genom observationer och intervjuer på fem olika avdelningar på sjukhuset har flertalet problem identifierats under informationsöverlämningen så som bristande syfte, avsaknad av agenda, ofokuserade deltagare, brist på uppföljning av information samt inkomplett kommunikation.
För att bemöta de problem som identifierats har följande rekommendationer tagits fram:
• Införande av både läsrapport och muntlig rapport
• Fastställande av mötestider
• Skapa anpassade mötesrum
• Skapa rollen mötessamordnare
• Framtagande av standardiserade checklistor
• Undersöka nuvarande visualiserande hjälpmedel
• Implementation av en kommunikationsmodel
Interior climate simulation of electric buses
No full textToday a large part of the power consumption for public transport vehicles is used
by the Heat, Ventilation and Air Conditioning, HVAC, system to ensure climate
comfort in the bus. In the transition to electrical vehicles it is of high importance to
reduce the HVAC systems power consumption. With electrical vehicles the power
consumption for the HVAC system is competing with the driving range for the
vehicle since there is a limited battery capacity. By simulating the interior climate
in buses investigations on how to reduce the power consumption of the HVAC
system can be done. Simulations enable that more parameters can be tested compared
with experimental testing.
In this master thesis a first draw of a method for simulating interior climate has
been developed. The method is based on CFD analyze of flow and temperature in
steady state. No passengers are included in the simulation and passengers comfort
are not taken into account. Important findings regarding meshing, boundary
conditions and physics models for the numerical CFD analyzis are presented. A
heat transfer coefficient, HTC, sweep has been performed to calibrate the simulation
model to experimental data
Same, Same, but Different - learning from references when designing contemporary brick architecture
No full text
Causes and Effects of Poor Demand Forecast Accuracy A Case Study in the Swedish Automotive Industry
No full textThis study is a part of a FFI (Fordonsstrategisk Forskning och Innovation) project “Future of
sharing schedule information in automotive industry supply chains using advanced data
analytics”. The study is aimed at describing the current situation in terms of accuracy of
demand forecasts sent from OEM companies to their suppliers within the Swedish automotive
industry, identifying root causes for inaccuracies in demand forecasts and their effect on the
suppliers. This study also aims to provide some guidance to future actions and initiatives for
improvement of demand forecast accuracy.
An extensive database of delivery schedules was used to identify current patterns in forecasting
accuracy, utilising FAI (Forecast Accuracy Index) to analyse forecasting performance. The
study employed a case methodology, studying three customers with a single supplier as the
focal point as a basis to find root causes and effects of poor forecasting accuracy.
The study found that current demand forecast accuracy was poor. Causes for poor performance
were found both in sales forecasts, that were used to generate the MPS and subsequently
component demand, and in the MRP systems of the customers. Inaccuracies in demand
forecasts were found to mainly be dealt with through buffers of materials and finished
components at the supplier. Improved forecasting accuracy is expected to allow suppliers to
lower their inventory levels, resulting in cost savings across the entire supply chain. This study
proposes evaluation of and changes to current MRP practices, closer integration of
complementary data in the sales forecasting process and employment of machine learning
algorithms in forecasting as promising areas for improving the accuracy of demand forecasts
