Risk analysis in manufacturing footprint decisions

A key aspect in the manufacturing footprint analysis is the risk and sensitivity analysis of critical parameters. In order to contribute to efficient industrial methods and tools for making well-founded strategic decisions regarding manufacturing footprint this paper aims to describe the main risks that need to be considered while locating manufacturing activities, and what risk mitigation techniques and strategies that are proper in order to deal with these risks. It is also proposed how the risk analysis should be included in the manufacturing location decision process

Industrial waste management within manufacturing: a comparative study of tools, policies, visions and concepts

Industrial waste is a key factor when assessing the sustainability of a manufacturing process or company. A multitude of visions, concepts, tools, and policies are used both academically and industrially to improve the environmental effect of manufacturing; a majority of these approaches have a direct bearing on industrial waste. The identified approaches have in this paper been categorised according to application area, goals, organisational entity, life cycle phase, and waste hierarchy stage; the approaches have also been assessed according to academic prevalence, semantic aspects, and overlaps. In many cases the waste management approaches have similar goals and approaches, which cause confusion and disorientation for companies aiming to synthesise their management systems to fit their waste management strategy. Thus, a study was performed on how waste management approaches can be integrated to reach the vision of zero waste in manufacturing

Production localization factors: an industrial and literature based review

Decision are commonly based on the available or easily accessible information; this is also true for more complex assessments like production localization. Where to locate production is often a key strategic decisions that has great impact on a company’s profitability for a long time; insufficient business intelligence may therefore have grave consequences. Six production localization factor studies have been assessed to see if they are focusing on the same issues and if there are any gaps. A new approach for structuring localization factors and the localization process is then presented and assessed with regards to some previously identified critical issues

Supply chain risks: an automotive case study

The supply chain is a complex system exchanging information, goods, material and money within enterprises, as well as between enterprises within the value chain. An effective supply chain management contributes to large corporate profits and it is therefore a valid path to reinforce the enterprises' competitiveness. However, supply chain is exposed to influences from undesirable factors both from the outside environment and the entities in the chain. Moreover, industrial trends towards lean production, increasing outsourcing, globalisation and reliance on supply networks capabilities and innovations, increase the complexity of the supply chain . Therefore, managers need to identify, and manage risks, as well as opportunities, from a more diverse range of sources and contexts. This paper contributes to identify and categorise supply chain risks based on a literature study and an automotive manufacturer’s viewpoint. The empirical results indicate suppliers and raw material prices as the major internal and external potential risks

Stability in quadratic variation

Consider a sequence of cadlag processes $\{X^n\}_n$, and some fixed function $f$. If $f$ is continuous then under several modes of convergence $X^n\to X$ implies corresponding convergence of $f(X^n)\to f(X)$, due to continuous mapping. We study conditions (on $f$, $\{X^n\}_n$ and $X$) under which convergence of $X^n\to X$ implies $\left[f(X^n)-f(X)\right]\to 0$. While interesting in its own right, this also directly relates (through integration by parts and the Kunita-Watanabe inequality) to convergence of integrators in the sense $\int_0^t Y_{s-}df(X^n_s)\to\int_0^t Y_{s-}df(X_s)$. We use two different types of quadratic variations, weak sense and strong sense which our two main results deal with. For weak sense quadratic variations we show stability when $f\in C^1$, $\{X^n\}_n,X$ are Dirichlet processes defined as in \cite{NonCont} $X^n\xrightarrow{a.s.}X$, $[X^n-X]\xrightarrow{a.s.}0$ and $\{(X^n)^*_t\}_n$ is bounded in probability. For strong sense quadratic variations we are able to relax the conditions on $f$ to being the primitive function of a cadlag function but with the additional assumption on $X$, that the continuous and discontinuous parts of $X$ are independent stochastic processes (this assumption is not imposed on $\{X^n\}_n$ however), and $\{X^n\}_n,X$ are Dirichlet processes with quadratic variations along any stopping time refining sequence. To prove the result regarding strong sense quadratic variation we prove a new It\^o decomposition for this setting

Stability in quadratic variation, with applications

We show that non continuous Dirichlet processes, defined as in \cite{NonCont} are closed under a wide family of locally Lipschitz continuous maps (similar to the time-homogeneous variants of the maps considered in \cite{Low}) thus extending Theorem 2.1. from that paper. We provide an It\^o formula for these transforms and apply it to study of how $[f(X^n)-f(X)]\to 0$ when $X^n\to X$ (in some appropriate sense) for certain Dirichlet processes $\{X^n\}_n$, $X$ and certain locally Lipschitz continuous maps. We also consider how $[f_n(X^n)-f(X)]\to 0$ for $C^1$ maps $\{f_n\}_n$, $f$ when $f_n'\to f'$ uniformly on compacts. For applications we give examples of jump removal and stability of integrators

Conditions for Innovation: Insights from a Multi-case Study

The paper is based on a multiple-case study of conditions for product-based innovations. Key actors from 18 cases were interviewed concerning the specific character of the innovation process, its parts and phases, with a focus on the realization phase. The cases are analyzed and discussed on the basis of an experience-based framework with seven specific components. In addition, the data are illustrated and discussed by more general themes of successful and unsuccessful innovation processes. It is concluded that the components of the used framework are necessary but individually not sufficient to maintain a continuous friction-free innovation process. The dynamics of the innovation processes are well illustrated by the framework