Planning Approach for Robust Manufacturing Footprint Decisions

TitlePlanning Approach for Robust Manufacturing Footprint Decisions
Publication TypeConference Paper
Year of Publication2014
AuthorsSprenger, P, Parlings, M, Hegmanns, T
EditorKersten, W, Blecker, T, Ringle, CM
Title of ProceedingsNext Generation Supply Chains
Volume18
Page29
Publisherepubli
Conference LocationHamburg
ISBN Number978-3-8442-9879-6; 978-3-7375-0340-2
ISSN NumberISSN (print) 2365-4430, ISSN (online) 2365-5070
KeywordsManufacturing Footprint Decision, Robustness, supply chain design, uncertainties
Abstract

The manufacturing footprint strategy of European automotive companies has
been determined in the preceding decades by a reduction of labour and
operational costs and the development of new markets. Today, the automotive
sector is characterised by growing number of logistic-related requirements like
customisation, just-in-sequence supply and assembly of vendor parts (FAST
2025, 2013). This leads to the development of footprint planning as a
multidimensional and complex decision problem with a significant impact on the
competitiveness and finances of the business (Häntsch and Huchzermeier,
2013; Farahani et al., 2013).
In response to this challenge, a literature review of footprint planning and facility
selection methods and models for designing supply chain networks will be
presented. The comparison of existing approaches shows the necessity of new
models that allow robust and adaptable footprint decisions while especially
considering project and market-related uncertainties. These uncertainties
demonstrate the need to revise the footprint strategy continuously.
Derived from the state-of-the-art analysis, a holistic planning work flow that
supports decision makers in automotive industries from a supply chain design
perspective with a special focus on the uncertainty of future business
opportunities is presented. This approach integrates qualitative planning
modules for knock-out-analyses and use-value-analyses and integrates
quantitative modules (e.g. Monte Carlo simulation) for future project allocation.
This planning procedure adopts a project-driven approach and allows for a
multidimensional evaluation of different footprint scenarios, based on an
uncertain future project and contract situation.