Discrete-event simulation and (mixed-integer) linear programming are widely used for supply chain planning. We present a general framework to support the operational decisions for supply chain networks using a combination of an optimi- zation model and discrete-event simulation. The simulation model includes nonlinear and stochastic elements, whereas the optimization model represents a simplified ver- sion. Based on initial simulation runs cost parameters, production, and transportation times are estimated for the optimization model. The solution of the optimization model is translated into decision rules for the discrete-event simulation. This procedure is applied iteratively until the difference between subsequent solutions is small enough. This method is applied successfully to several test examples and is shown to deliver competitive results much faster compared to conventional mixed-integer models in a stochastic environment. It provides the possibility to model and solve more real- istic problems (incorporating dynamism and uncertainty) in an acceptable way. The limitations of this approach are given as well.

/pdf/simulation-and-optimization-of-supply-chains-alternative-or-4pto12z99r.pdf

Simulation and optimization of supply chains: alternative or complementary approaches?

Planning and scheduling in the automotive industry: A comparison of industrial practice at German and Japanese makers

Reconciling sales and operations management with distant suppliers in the automotive industry: A simulation approach

This study presents a systematic literature review of the recent scholarly literature on product complexity (number, diversity, and interrelatedness of product variants and components) and operational performance (measured in terms of cost, time quality, and delivery reliability) in manufacturing and supply chain firms, considering the manufacturing context as well as the mechanisms behind the relationships. The results show that product complexity has a consistently negative relationship with cost, time, quality, and delivery performance measures, though the relationships with quality and delivery performance are less clear.

Product complexity and operational performance: A systematic literature review

Product, process and customer preference alignment in prefabricated house building

Purpose – The purpose of this paper is to challenge the common claim of “infinite variety” being demanded in the marketplace by measuring not just how much variety theoretically could be produced, but how much is actually demanded by the customer. To this effect, the authors propose and validate market‐based variety measures with empirical data and in a second step, extend their analysis by applying these measures and empirically testing the impact of variety mitigation strategies, such as postponement and options bundling.Design/methodology/approach – The authors analyse production and sales data of 226,106 passenger cars, comprising of three models of one vehicle manufacturer sold across four global market regions. The theoretical variety is compared with actual variety for each model‐market combination, and these data are linked to actual production and sales records.Findings – The authors propose and validate product variety measures based on actual customer orders, and empirically demonstrate how the...

Theoretical versus actual product variety: how much customisation do customers really demand?

In many industries, the frequency of production ramp-ups has increased due to shorter product life cycles and increased product variety. Production often takes place at globally dispersed facilities for customers in multiple markets, for example, in the automotive industry. Therefore, ramp-up planning must be carried out for a network. The planning problem at hand is to simultaneously optimise the allocation of products of a common product platform to plants, the timing of ramp-ups and ramp-downs, ramp-up duration and shape of capacity and production and transportation volumes with respect to the net present value of the profit. We develop a hierarchical planning framework and place strategic ramp-up planning therein. We provide a mixed integer programming model for this planning problem. Following the example of a German car manufacturer in the premium segment, we conduct a numerical analysis to obtain insights into optimal ramp-up and ramp-down decisions. The results show that it could be beneficial to ...

Strategic ramp-up planning in automotive production networks

This paper introduces an approach for highly efficient simulation of supply networks. The approach is based on a combination of artificial intelligence and continuous simulation concepts. It is motivated by project requirements from various Supply Chain Management projects in the automotive industry. From artificial intelligence, the concept of agent-based modelling is adopted. From continuous simulation, the approach of time-step based development of state-space models is borrowed. Combined and enriched with features for mapping specific processes in automotive industry, these concepts yielded in a highly efficient supply network simulation approach which was successfully used in several business applications and research projects. The Supply Net Simulator SNS will be introduced by presenting its basic concept, software architecture, and some application examples.

The Supply Net Simulator SNS: An Artificial Intelligence Approach for Highly Efficient Supply Network Simulation

The purpose of this paper is to challenge the common claim of "infinite variety" being demanded in the marketplace by measuring not just how much variety theoretically could be produced, but how much is actually demanded by the customer. To this effect, the authors propose and validate market-based variety measures with empirical data and in a second step, extend their analysis by applying these measures and empirically testing the impact of variety mitigation strategies, such as postponement and options bundling. The authors analyse production and sales data of 226,106 passenger cars, comprising of three models of one vehicle manufacturer sold across four global market regions. The theoretical variety is compared with actual variety for each model-market combination, and these data are linked to actual production and sales records. The authors propose and validate product variety measures based on actual customer orders, and empirically demonstrate how these measures can be used to assess the impact of late configuration and option bundling strategies, and find that these are generally valid, but that their applicability is contingent upon the respective variety distribution profile. Analyses are developed within the context of a single firm and industry, although an attempt was made to counter this weakness by considering models from the volume, niche and premium market segments. The paper highlights how actual variety differs from theoretical variety in practice, which in turn co-determines the effectiveness of mitigation strategies applied by firms. The paper's main contribution is to propose and empirically test a set of novel measures of product variety: the average repetition ratio and a specification Pareto curve, both of which complement and enhance one's understanding of product variety and its impact on manufacturing and distribution systems.

Theoretical versus actual product variety: How much customisation do customers really demand?

The method involves producing multiple pieces in a predetermined completion period. A determination is made in computer based shape, which determines in which portion of the piece of the technical system an attribute accepts a certain attribute value. A set of computer based writings of respective configuration of multiple pieces of the technical system is determined. An optimization is executed, where weighting factors are used as variables of the optimization. A composition of determined portion-distances is used as target function concerning the determinations. Each weighting factor concerns a system piece produced in reference period. The portion-distance concerns a determination of the distance between the determined portion and the portion of the piece-configuration weighted with the weighting factors. A partially required determination is executed by using the piece-writing. The computed numbers of component-pieces are multiplied with the optimal weighting factor for the system-piece. The component-piece-numbers are summed by all system-pieces and the number of the pieces of this component part required in completion period is computed by using the sum which is computed for the component part. Independent claims are also included for the following: (1) a digital storage medium has electronically selected control (2) a data processing plant for the production planning for a technical system.

Method for production planning for technical system, involves producing multiple pieces in predetermined completion period, where determination is made in computer based shape

Thomas Stäblein

Papers

Theoretical versus actual product variety: how much customisation do customers really demand?

Strategic ramp-up planning in automotive production networks

The Supply Net Simulator SNS: An Artificial Intelligence Approach for Highly Efficient Supply Network Simulation

Theoretical versus actual product variety: How much customisation do customers really demand?

Method for production planning for technical system, involves producing multiple pieces in predetermined completion period, where determination is made in computer based shape