Tommaso Rossi

Bullwhip effect and inventory oscillations analysis using the beer game model

This work examines the bullwhip effect generated and suffered by each level of a four-stage beer game supply chain when different demand scenarios are considered. The paper shows that the actors who generate lower bullwhip are those who suffer more from its effects. Moreover, a new definition of an inventory oscillations measure based on bullwhip definition is introduced. Finally the paper verifies that the new measure of inventory oscillations provides more information on supply chain performance than the bullwhip measure.

Managing operational risks along the oil supply chain

Operational risk in the oil industry may lead to environmental disasters and to heavy loss of human lives. However, the relationship between operational risk and oil supply chain management is poorly studied. This article proposes a model (derived from the Enis supply chain) to analyse and to assess the operational risk at the drilling, primary transport and refining stage of the oil supply chain. For the drilling stage, the model suggests three sub-methods, one for each period of the plant life cycle (design, construction and production). For the primary transport stage, two different risk management processes are proposed: the former one allows the risks resulting from processes, procedures and physical components (other than oil-pipelines) to be identified, assessed and controlled, whereas the latter one allows risks arising from the pipeline breakdowns to be faced. Finally, for the refining stage, a preliminary phase is recommended to prioritise each equipment of the refinery, and several techniques and tools are suggested.

Evaluating supply chain integration: a case study using fuzzy logic

This paper aims at investigating a new methodology to evaluate supply chain integration by applying the fuzzy sets theory. Fuzzy sets proved successful in environments similar to supply chain management in that they help to formalise human reasoning patterns and to develop high-performance expert systems in contexts where data are affected by uncertainty and/or vagueness: e.g. fuzzy sets have been already used in inventory planning, to improve organisational effectiveness, to perform suppliers’ evaluation etc. In particular, the study presented here deals with the ways to measure and achieve supply chain integration and it mainly focuses on the external integration (i.e. on the ability to leverage partnerships within the chain), clustered in two areas, i.e. the network design and the management policies. The new methodology has been applied to a case study which consists of a 3-stage supply chain belonging to the beauty and personal care industry. Results of the case-study indicate that the companies still have important edges for improvement towards a complete integration of their supply processes. In particular, the considered supply chain should prioritise the integration of technology-driven investments and in the distribution area.

An integrated model for designing and optimising an international logistics network

Supply-chain configuration has recently gained increasing attention both from the practitioners perspective and as a research area. This paper proposes an integrated model for designing and optimising international logistics networks. It consists of a mixed integer linear programming model and a data-mapping section (i.e. methodological guidelines for gathering and processing the data necessary to set up the model). It has been specifically developed for solving the configuration problem for supply chains characterised by a complexity level typical of real-life global logistics networks. Although this topic is well understood and well elaborated at a technical level in the extant literature, it still presents obstacles in practice especially in terms of dealing with real-life complexity, service-level constraints and data mapping. Thus, we developed our integrated approach with the aim to fill these gaps. We designed our model for dealing with multiple-layer, single location-layer, multiple-commodity and time-constrained logistics networks, to be implemented in a single period time horizon and in a deterministic environment. The proposed approach represents an innovative contribution to the existing body of scientific knowledge and facilitates the data gathering and processing activities, which are largely recognised as complex and time-consuming processes for the management of logistics activities.

Linking supply chain configuration to supply chain perfrmance: A discrete event simulation model

Abstract This paper aims to analyse the dependencies between supply chain performance, i.e. stock and stock-outs, and both supply chain management decisions and supply chain configuration parameters, i.e. the number of sources, the inventory capacity at a given node and the number of nodes that share the considered inventory capacity, the distance between nodes and the number of levels of the supply chain. The relationships among these variables have been studied by means of a scenario design technique and the discrete event simulation together with statistical analysis. Models of Economic Order Quantity (EOQ)-based and forecast-based supply chains have been developed. Results suggest some managerial implications potentially useful in field: intermediaries and specialized actors (either global or local – since the distance proved to be irrelevant) can be added for the sake of product quality and cost, without adversely affecting service level performance at the retailer stage. Collaborative practices are proved to be very helpful, especially when the number of sources increases. However, retailers’ performance enhance, while distributors’ one and manufacturers’ one worsen, thus raising hurdles to collaborate.

A formal method for analysing and assessing operational risk in supply chains

This paper formalises an objective method to identify and assess operational risk in supply chains. The proposed approach exploits the analogy among logistics networks and dynamical systems. In particular, risky events identification is based on the analysis of the coverability graph of the timed attributed Petri net describing the analysed supply chain, whereas risk assessment is done by building the simulation model of the studied logistic network, experimenting on it and applying ANOVA to analyse the results and evaluating the importance among the risky events previously figured out. The method has been applied to an example case represented by a single-item, three-stage supply chain.

Applying an integrated logistics network design and optimisation model: the Pirelli Tyre case

The aim of the present paper is to provide an application to a real-life supply-chain context (i.e. the Pirelli Tyre European logistics network) of an integrated logistics network design and optimisation model. Starting from the analysis of supply chain under study and of the configuration problem to be solved, we identified the most suitable approach: a mixed integer linear programming optimisation model endowed with a series of guidelines for gathering and processing all the data necessary to set-up and run the model. The application of the selected integrated design and optimisation model to the Pirelli Tyre case led to significant cost savings related to three different service-level scenarios. Thus, the applied model could be profitably implemented by supply chain and logistics managers for optimising various operating contexts. Moreover, the exemplified data-mapping section represents a useful guideline, which can be applied by practitioners to gather and handle the high volume of data necessary for running the model in a real-life context. In conclusion, since the current state of the art is particularly lacking exhaustive supply-chain design models, the implemented integrated approach represents a significant contribution to the existing body of knowledge on supply chain configuration.

RFID technology for increasing visibility in ETO supply chains: a case study

This paper presents the application of an innovative system for increasing visibility along an Engineer-To-Order supply chain. The system has been applied in a leading Italian company that manufactures vessels and tube heat exchangers. By means of this method, the company shares information about its shop floor activities with other actors in the supply chain, i.e. clients and suppliers. The system elements are as follows: Radio-frequency identification transponders (to identify either components, operators, tooling machines (e.g. welding machines) or production phases), a Wi-Fi network (to communicate data) and a web-based application that is accessible by the company’s clients. This paper shows the methodology that is used to define the system’s architecture and the technical solutions adopted. Benefits in terms of reduction in costs for monitoring and control have been observed. Moreover, customers perceived the increased visibility of the production process to be a valuable service.

Improving productivity of automated tissue converting lines: an empirical model and a case study

This study is focused on minor stoppages as sources of variance within automated production lines in industrial environments, and it suggests the handling of the problem through a combined phenomenon–mechanism analysis and simulation approach. The resulting seven-step methodological pattern has been applied to a real-life case study of a tissue converting line: the product type and the machine speed have been identified as causal factors for minor stoppages and the wrapper machine has been chosen to exemplify the methodology.  In turn, it consists of four sub-steps: (i) identifying operating principles; (ii) identifying operating standards; (iii) identifying interacting elements; (iv) quantifying physical changes involved. Results point out that the speed of the wrapping machine–which allows the daily throughput of line to be maximized–changes when products change, thus highlighting a trade off between minor stoppages and wrapper speed. However, in some other cases, minor stoppages are more detrimental than the machine speed is useful.

An object-oriented simulation meta-model to analyse supply chain performance

This paper proposes a meta-model, which allows automatic building of simulation models of supply chains. The proposed meta-model is made up from a user interface (to define the characteristics of the supply chain), an ad hoc objects library and a software application, to build the simulation model. The meta-model can dramatically reduce to a few minutes or even seconds the time required to test a specific configuration of a supply chain and/or a specific management policy and, since the simulation model is automatically built, neither the personnel skills nor the time available to build the simulation model represent significant hurdles anymore. The meta-model has been applied to represent a simplified supply chain according to six different scenarios, where demand is deterministic. For each scenario a simulation campaign has been performed and the outputs of the model (built through the proposed meta-model) correspond to the predicted results.