An optimisation framework for improving supply chain performance: case study of a bespoke service provider

A service supply chain can be described as a system of systems with a highly interactive and complex network of suppliers, service providers, OEMs and customers. Supply chain management could create value for bespoke service providers, customers and stakeholders cooperating through the supply chain. Bespoke service provider companies are responsible for managing their asset based on different service contracts and possibly through the end of the asset lifetime. Providing a through-life service requires tailored strategic dimensions to measure the supply chain performance. The performance can be evaluated with regards to several supply chain elements such as demand management, procurement, logistics, etc. This article takes a different angle to the current supply chain performance frameworks by discussing performance through DMAIC cycle. Considering a through-life service, this paper presents a performance optimization framework to improve the supply chain performance in terms of an asset or component availability and cost of service. Moreover, an exhaustive list of KPIs to evaluate the supply chain performance are identified. A case study of fleet management for a bespoke service provider is considered to test the validity of the framework. The DMAIC technique has demonstrated to be an effective method to improve supply chain strategies and performance.Cranfield Universit

Shared heritability and functional enrichment across six solid cancers

Correction: Nature Communications 10 (2019): art. 4386 DOI: 10.1038/s41467-019-12095-8Quantifying the genetic correlation between cancers can provide important insights into the mechanisms driving cancer etiology. Using genome-wide association study summary statistics across six cancer types based on a total of 296,215 cases and 301,319 controls of European ancestry, here we estimate the pair-wise genetic correlations between breast, colorectal, head/neck, lung, ovary and prostate cancer, and between cancers and 38 other diseases. We observed statistically significant genetic correlations between lung and head/neck cancer (r(g) = 0.57, p = 4.6 x 10(-8)), breast and ovarian cancer (r(g) = 0.24, p = 7 x 10(-5)), breast and lung cancer (r(g) = 0.18, p = 1.5 x 10(-6)) and breast and colorectal cancer (r(g) = 0.15, p = 1.1 x 10(-4)). We also found that multiple cancers are genetically correlated with non-cancer traits including smoking, psychiatric diseases and metabolic characteristics. Functional enrichment analysis revealed a significant excess contribution of conserved and regulatory regions to cancer heritability. Our comprehensive analysis of cross-cancer heritability suggests that solid tumors arising across tissues share in part a common germline genetic basis.Peer reviewe

Shared heritability and functional enrichment across six solid cancers

Quantifying the genetic correlation between cancers can provide important insights into the mechanisms driving cancer etiology. Using genome-wide association study summary statistics across six cancer types based on a total of 296,215 cases and 301,319 controls of European ancestry, here we estimate the pair-wise genetic correlations between breast, colorectal, head/neck, lung, ovary and prostate cancer, and between cancers and 38 other diseases. We observed statistically significant genetic correlations between lung and head/neck cancer (r(g) = 0.57, p = 4.6 x 10(-8)), breast and ovarian cancer (r(g) = 0.24, p = 7 x 10(-5)), breast and lung cancer (r(g) = 0.18, p = 1.5 x 10(-6)) and breast and colorectal cancer (r(g) = 0.15, p = 1.1 x 10(-4)). We also found that multiple cancers are genetically correlated with non-cancer traits including smoking, psychiatric diseases and metabolic characteristics. Functional enrichment analysis revealed a significant excess contribution of conserved and regulatory regions to cancer heritability. Our comprehensive analysis of cross-cancer heritability suggests that solid tumors arising across tissues share in part a common germline genetic basis

Distributed field services - simulation and operational performance

Among the key technologies of the fourth industrial revolution, connectivity, internet of things, big data and analytics are frequently used to drive performance improvements for products, processes, and services. In this context, a key contributor to achieving competitive services is the ability to define appropriate practices to optimise services. A key challenge is to deliver actionable analytics, i.e. outcomes that can lead to action recommendations.This project focuses on the area of distributed field services and in particular on the way to link connected field services with performance analytics and evaluate performance benefits through simulation, optimised on the basis of operational data. Such an approach can bring many benefits to businesses, both at strategic and tactical levels, offering potential to consider different scenarios and evaluate how the business will react and perform, leading to action recommendations.A simulation-basedapproach has been developed to optimise the size and distribution of field service workforce. This has been applied on an industrial case study involving real dat

Distributed field services - simulation and operational performance

Among the key technologies of the fourth industrial revolution, connectivity, internet of things, big data and analytics are frequently used to drive performance improvements for products, processes, and services. In this context, a key contributor to achieving competitive services is the ability to define appropriate practices to optimise services. A key challenge is to deliver actionable analytics, i.e. outcomes that can lead to action recommendations.This project focuses on the area of distributed field services and in particular on the way to link connected field services with performance analytics and evaluate performance benefits through simulation, optimised on the basis of operational data. Such an approach can bring many benefits to businesses, both at strategic and tactical levels, offering potential to consider different scenarios and evaluate how the business will react and perform, leading to action recommendations.A simulation-basedapproach has been developed to optimise the size and distribution of field service workforce. This has been applied on an industrial case study involving real dat

Distributed field services - simulation and operational performance

Among the key technologies of the fourth industrial revolution, connectivity, internet of things, big data and analytics are frequently used to drive performance improvements for products, processes, and services. In this context, a key contributor to achieving competitive services is the ability to define appropriate practices to optimise services. A key challenge is to deliver actionable analytics, i.e. outcomes that can lead to action recommendations.This project focuses on the area of distributed field services and in particular on the way to link connected field services with performance analytics and evaluate performance benefits through simulation, optimised on the basis of operational data. Such an approach can bring many benefits to businesses, both at strategic and tactical levels, offering potential to consider different scenarios and evaluate how the business will react and perform, leading to action recommendations.A simulation-basedapproach has been developed to optimise the size and distribution of field service workforce. This has been applied on an industrial case study involving real dat

Multidisciplinary Mathematical Modelling: Applications of Mathematics to the Real World

Peer ReviewedPostprint (published version

Shared heritability and functional enrichment across six solid cancers

Quantifying the genetic correlation between cancers can provide important insights into the mechanisms driving cancer etiology. Using genome-wide association study summary statistics across six cancer types based on a total of 296,215 cases and 301,319 controls of European ancestry, here we estimate the pair-wise genetic correlations between breast, colorectal, head/neck, lung, ovary and prostate cancer, and between cancers and 38 other diseases. We observed statistically significant genetic correlations between lung and head/neck cancer (rg = 0.57, p = 4.6 × 10−8), breast and ovarian cancer (rg = 0.24, p = 7 × 10−5), breast and lung cancer (rg = 0.18, p =1.5 × 10−6) and breast and colorectal cancer (rg = 0.15, p = 1.1 × 10−4). We also found that multiple cancers are genetically correlated with non-cancer traits including smoking, psychiatric diseases and metabolic characteristics. Functional enrichment analysis revealed a significant excess contribution of conserved and regulatory regions to cancer heritability. Our comprehensive analysis of cross-cancer heritability suggests that solid tumors arising across tissues share in part a common germline genetic basis