A.J.M. Beulens

Identifying sources of uncertainty to generate supply chain redesign strategies

Dynamic demands and constraints imposed by a rapidly changing business environment make it increasingly necessary for companies in the food supply chain to cooperate with each other. The main questions individual (food) companies face are whether, why, how and with whom they should start supply chain management activities. Presents a qualitative research method for analyzing a supply chain network and for identifying effective chain redesign strategies. Presents a generic list of supply chain redesign strategies based on a multi‐disciplinary literature review. Proposes that in order to identify the most effective strategies in a specific chain scenario one should focus on the identification and management of the sources of uncertainties in the supply chain’s decision‐making processes. The application of the research method in three food supply chains resulted in a valuable tool that can be used in supply chain redesign projects, as it indicates potentially effective redesign strategies when a specific source of uncertainty is encountered in a supply chain.

Modelling and simulating multi-echelon food systems

This paper presents a method for modelling the dynamic behaviour of food supply chains and evaluating alternative designs of the supply chain by applying discrete-event simulation. The modelling method is based on the concepts of business processes, design variables at strategic and operational levels, performance indicators, and business entities, as these concepts allow relevant aspects of a food supply chain to be described and modelled. Our simulation model is based on timed coloured Petri-nets to support decision-making when redesigning a supply chain for chilled food products. Scenario analysis allowed us to evaluate the potential benefits of alternative designs for this supply chain in terms of logistical performance. In this case study, major benefits were identified. The results of the scenario analysis are compared with the outcomes of a pilot project where one scenario was implemented in real life.

A methodology to support multidisciplinary model-based water management

Quality assurance in model based water management is needed because of some frequently perceived shortcomings, e.g. a lack of mutual understanding between modelling team members, malpractice and a tendency of modellers to oversell model capabilities. Initiatives to support quality assurance focus on single domains and often follow a textbook approach with guidelines and checklists. A modelling process involves a complex set of activities executed by a team. To manage this complex, usually multidisciplinary process, to guide users through it and enhance the reproducibility of modelling work a software product has been developed, aiming at supporting the full modelling process by offering an ontological knowledge base (KB) and a Modelling Support Tool (MoST). The KB consists of a generic part for modelling, but also parts specific for various water management domains, for different types of users and for different levels of modelling complexity. MoSTs guiding component filters relevant knowledge from the KB depending on the user profile and needs. Furthermore, MoST supports different types of users by monitoring what they actually do and by producing customized reports for diverse audiences. In this way MoST facilitates co-operation in teams, modelling project audits and re-use of experiences of previous modelling projects.

Supply Chain Design in the Food Industry

The concepts of hybrid supply chain strategies and the decoupling point are applied to a poultry supply chain experiencing high demand uncertainty in an inflexible production environment. Several solutions are proposed for this supply chain to cope with high demand uncertainty. The customer order decoupling point, the product differentiation point and the information decoupling point play a central role in these solutions. Because of specific characteristics of the poultry supply chain, the opportunities for a leagile supply chain design are limited.

Simulation model of multi-compartment distribution in the catering supply chain

Abstract An efficient distribution system of high performance is needed to anticipate market developments in the catering supply chain (CSC) in the Netherlands. A simulation model was developed to analyse a multi-compartment distribution system which should satisfy customer demands for shorter lead times, increased delivery frequency and improved quality of process and product. The simulation model quantifies logistic and financial performances in various alternative logistic scenarios for multi-compartment distribution in the catering supply chain. This stochastic simulation model was constructed on the basis of a value chain analysis yielding activities and performance indicators (PIs). The model proved to be accurate in its predictions when applied to a case situation taken from the Dutch CSC. It is concluded that discrete event simulation is an effective tool to evaluate promising logistic scenarios. The new, multi-compartment method of distribution allowed for a 14% decrease in total costs in the Dutch CSC while satisfying customer demands.

Validation of an agent-based model for spatial planning: A role-playing approach

This paper discusses the validation of an agent-based model for simulating a multi-actor spatial planning process. After a general discussion about the pitfalls of validating agent-based models that simulate complex spatial systems, we briefly present a validation method based on role playing. The method is designed to generate insights that can improve our understanding of the behaviour of socio-spatial systems in a planning context. The method was tested by carrying out an experimental role play to validate individual agent tasks, focusing on the ability of agents to generate beliefs and preferences about their environment. We conclude that using role play as a validation technique can provide valuable information about the performance of the model. The insights gained aid identification and understanding of those parts of a multi-actor spatial planning system that are currently poorly understood and poorly represented by the agents.

Towards dynamic reference information models: Readiness for ICT mass customisation

Current dynamic demand-driven networks make great demands on, in particular, the interoperability and agility of information systems. This paper investigates how reference information models can be used to meet these demands by enhancing ICT mass customisation. It was found that reference models for Production and Supply Chain Management do not yet sufficiently meet the requirements of a mass customisation approach. They have developed from isolated models based on pure standardisation and tailored customisation strategies, towards static repository-based models founded on segmented standardisation strategies. Existing models provide valuable knowledge for developing towards more dynamic reference information models, including the progress made by ERP vendors to make their reference models configurable. Important remaining challenges are setting up reference information models as generic models that define classes of architectures, and incorporating user-friendly means that guide users through the process of configuring specific information models.

A framework for early warning and proactive control systems in food supply chain networks

It is inherent to food supply chain networks that performance deviations occur occasionally due to variations in product quality and quantity. To reduce losses, one wants to be informed about such deviations as soon as possible, preferably even before they occur. Then it is possible to take actions to prevent or reduce negative consequences. In practice, extensive operational data is recorded, forming a valuable source for early warning and proactive control systems, i.e. decision support systems for prediction and prevention of such performance problems. Data mining methods are ideal for analyzing such data sources and extracting useable information from them. In this paper, we present a novel framework for early warning and proactive control systems that combine expert knowledge and data mining methods to exploit recorded data. We discuss the implementation of a prototype system and the experiences from a case study regarding the applicability of the framework.

Simulating Knowledge Sharing in Spatial Planning: An Agent-Based Approach:

This paper presents a multiagent system (MAS) that simulates a multiactor interactive spatial-planning process. The MAS extends an existing approach with the principle of sharing knowledge between participating actors while trying to create a shared vision. In the simulation, actors are modelled as agents. They have desires and preferences regarding the future development of their environment. These are used to develop their individual views on what areas are eligible for change. A facilitator agent coordinates the exchange of information by indicating possible solutions and conflicts to the actor agents. The simulation is demonstrated for an allocation problem in a pilot area in the southeast of the Netherlands. Four different scenarios are implemented, which demonstrate the impact of cooperation and hierarchy during an interactive spatial-planning process. Although the model is kept limited in terms of input data, the results show its potential for providing insight into the relations and interaction between actors, rather than predicting the results of an interactive spatial-planning process.

Mastering demand and supply uncertainty with combined product and process configuration

The key challenge for mastering high uncertainty of both demand and supply is to attune products and business processes in the entire supply chain continuously to customer requirements. Product configurators have proven to be powerful tools for managing demand uncertainty. This paper assesses how configurators can be used for combined product and process configuration in order to support mastering high uncertainty of both supply and demand. It defines the dependence between product and process configuration in a typology of interdependencies. The addressed dependences go beyond the definition phase and also include the effects of unforeseen backend events during configuration and execution. Based on a case study in the Dutch flower industry, a conceptual architecture is proposed for coordination of these interdependencies and development strategies are identified.