Previously published as: Benchmarking for Quality Management & Technology
Online from: 1999
Subject Area: Accounting and Finance
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|Title:||Maintenance performance indicators (MPIs) for benchmarking the railway infrastructure: A case study|
|Author(s):||Thomas Åhrén, (Division of Operation and Maintenance Engineering, Luleå University of Technology, Luleå, Sweden), Aditya Parida, (Division of Operation and Maintenance Engineering, Luleå University of Technology, Luleå, Sweden)|
|Citation:||Thomas Åhrén, Aditya Parida, (2009) "Maintenance performance indicators (MPIs) for benchmarking the railway infrastructure: A case study", Benchmarking: An International Journal, Vol. 16 Iss: 2, pp.247 - 258|
|Keywords:||Benchmarking, Costs, Maintenance, Performance management, Railways, Sweden|
|Article type:||Case study|
|DOI:||10.1108/14635770910948240 (Permanent URL)|
|Publisher:||Emerald Group Publishing Limited|
|Acknowledgements:||This study was performed within Luleå Railway Research Centre (JvtC), and the authors gratefully acknowledge the support from Banverket and Jernbaneverket in terms of information and funding. The authors would also like to thank Ulla Espling for support during the case studies.|
Purpose – For railway infrastructure, benchmarking is an effective tool that can support the management in their pursuit of continuous improvement by the use of maintenance performance indicators (MPIs). Hence, there is a need to study the MPIs and link them with benchmarking. The purpose of this paper is to present case studies dealing with the application of benchmarking and maintenance performance indicators for the railway infrastructure.
Design/methodology/approach – Case studies were conducted at Banverket (the Swedish Rail Administration) and at Jernbaneverket (the Norwegian National Rail Administration), which is responsible for the Norwegian part of the Iron Ore Line between Kiruna in Sweden and Narvik in Norway. The results from the two case studies are compared and analyzed. The benchmarking data for the railway infrastructure are retrieved, classified and analyzed for best practice improvement.
Findings – MPIs can successfully use benchmarking as a tool for improvement by learning from within or from other organizations for continuous improvement, which is a rather new phenomenon in the railway industry.
Research limitations/implications – Each railway infrastructure is unique due to its geographical locations and constraints, besides the organization, management and other resources. These factors need to be considered while benchmarking the railway infrastructures.
Practical implications – The results obtained in these case studies can be used by the railway infrastructure managers for continuous improvements. Moreover, other relevant MPIs required by the railway infrastructure managers can be benchmarked in a similar manner.
Originality/value – The paper presents a structured method for continuous improvement of railway infrastructure by using MPIs for benchmarking.
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