Analysing distribution operations using the methods of Lean Six Sigma for Company X
Spiridonova, Ekaterina (2017)
Spiridonova, Ekaterina
Haaga-Helia ammattikorkeakoulu
2017
All rights reserved
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:amk-2017121320896
https://urn.fi/URN:NBN:fi:amk-2017121320896
Tiivistelmä
In today’s highly competitive market, logistics companies must strive to achieve excellence in distribution services to win a market share. This requires logistics companies to boost their service quality and cut costs by improving performance through process optimization, loss elimination and waste reduction. Lean and Lean Six Sigma methods have proved to be effective in helping companies achieve these goals.
This Thesis is based on the author’s Lean Six Sigma (LSS) Black Belt project commissioned by Company X. The scope of the project was limited to Company X’s distribution operations, particularly van loading and delivery processes, in the Helsinki metropolitan area from Terminal Y for four months period, from September to December 2016. This project aimed to provide improvement opportunities for Company X to reduce additional deliveries of the same package using Lean Six Sigma analytical methods.
The theoretical framework consists of three aspects: describing distribution processes of Company X, and discovering a LSS project management approach known as Define-Measure-Analyse-Improve-Control (DMAIC) and LSS tools for data analysis to draw conclusions. The literature review built a theoretical foundation for process analysis, while observations and interviews with workers were made to obtain reliable and valid practical information on process work in Terminal Y. Data analysis on failed deliveries and van loading efficiency was conducted using Exploratory Data Analysis (EDA). In particular the following tools were used: I-Charts, Probability Chart, Process Capability Analysis, Analysis of Variance ANOVA and Pareto chart.
Improvement opportunities were identified and validated in three operational areas: inbound flow, terminal handling, van loading and outbound delivery routing to customers. Other recommendations were made regarding planned improvements to Company X’s distribution infrastructure and software, planned for near term capital investment.
This Thesis is based on the author’s Lean Six Sigma (LSS) Black Belt project commissioned by Company X. The scope of the project was limited to Company X’s distribution operations, particularly van loading and delivery processes, in the Helsinki metropolitan area from Terminal Y for four months period, from September to December 2016. This project aimed to provide improvement opportunities for Company X to reduce additional deliveries of the same package using Lean Six Sigma analytical methods.
The theoretical framework consists of three aspects: describing distribution processes of Company X, and discovering a LSS project management approach known as Define-Measure-Analyse-Improve-Control (DMAIC) and LSS tools for data analysis to draw conclusions. The literature review built a theoretical foundation for process analysis, while observations and interviews with workers were made to obtain reliable and valid practical information on process work in Terminal Y. Data analysis on failed deliveries and van loading efficiency was conducted using Exploratory Data Analysis (EDA). In particular the following tools were used: I-Charts, Probability Chart, Process Capability Analysis, Analysis of Variance ANOVA and Pareto chart.
Improvement opportunities were identified and validated in three operational areas: inbound flow, terminal handling, van loading and outbound delivery routing to customers. Other recommendations were made regarding planned improvements to Company X’s distribution infrastructure and software, planned for near term capital investment.