Six Sigma in Urban Logistics Management—A Case Study

The Influence of Sample Size on Long-Term Performance of a 6σ Process

There are many criticisms for the association between the Six Sigma concept and the two statistical metrics associated to 6σ processes: 1.5σ shift for maximum deviation and 3.4 PPM non-conformities for the long-term performance. As a result, the paper aims to carry out an analysis of this problem, and the first result obtained is that a stable process can reach a maximum drift, but its value depends on the volume of the sample. It is also highlighted that, using only the criterion “values outside the control limits” for monitoring stability through the Xbar chart, a minimum value can be calculated for the long-term performance of a process depending on the sample size. The main conclusion resulting from the calculations is that, in the case of a 6σ process, the long-term performance is much better than the established value of 3400 PPB: For small volume samples of two pieces it is below 700 PPB, for three pieces it is below 200 PPB, and for samples with a volume greater than or equal to four pieces the performance already reaches values below 100 PPB! So, the long-term performance of 6σ processes is certainly even better than the known value of 3.4 PPM.

Methodology for Prioritizing Best Practices Applied to the Sustainable Last Mile—The Case of a Brazilian Parcel Delivery Service Company

The ever-increasing impacts of the last mile delivery sector on the environment and the quality of life of the urban population, such as increased congestion, demand best practices to be incorporated by companies to reduce impacts such as emission of air pollutants and Greenhouse Gases (GHG) and depletion of natural resources, among others. However, a myriad of strategies has been developed for this purpose but there is a lack of methodologies that allow the choice of the best ones for a specific case. Therefore, this study looks for those best practices to be employed through an innovative methodology that consists of SWOT analysis (Strengths, Weaknesses, Opportunities, and Threats), a map of strategies of the delivery service, and using the Sustainability Balanced Scorecard (SBSC) and the Analytic Hierarchy Process (AHP), with the differential of considering the peculiarities of each company. The results applied in a Brazilian last mile delivery service company show that best practices such as route optimization, implementation of new infrastructure and business models for urban deliveries, and use of information systems for fleet tracking and monitoring contribute significantly to improving performance indicators and achieving the sector’s goal to become more sustainable, and especially meeting the Sustainable Development Goals (SDGs) 8, 9, 11, and 17.