Simulation model of the logistic distribution in a medical oxygen supply chain

Research activities on operations management in the last years are always more dedicated to supply chain and logistics optimization models. The study belongs to this branch and describes the problems related to a re-configuration of the distribution net in a company that produces medical oxygen cylinders for Italian market. The enterprise is particularly sensible to the optimization of supplying processes due to the characteristics of its product, as any delay in the delivery could create dangerous health situation for patients. The work has the objective to realize a software for supply chain management that could be a decision support system, analyzing strategic impacts that changes in distribution system create. In details, the model shows the differences in service level in case of closing one or more factories and the relative necessary changes in logistics net. The paper is articulated in the following parts: • analysis of company and construction of simulation model; • study of classic operation research techniques to solve dynamic vehicle routing problems; • description of possible scenes derived by strategic decision in closing factories; analysis of experiments and global conclusions and developments

Supply Chain Leadership

The complexity found in supply chains draws on the combined capabilities of multiple firms. Success in this environment requires the coordinated efforts of both a supply chain leader organization, and one or more supply chain follower organizations. Supply chain leadership has traditionally been ascribed to the most powerful, dominant organization in the supply chain. The theory of supply chain leadership presented in this dissertation redefines leadership in the supply chain context as a relationship between leader and followers described by the behaviors exhibited through each organization’s actions. The theoretical model was developed from literature in the leadership, logistics, and strategic management disciplines. The nomological network is derived from five constructs: supply chain leadership, supply chain followership, information availability, communications, and rewards. Empirical testing was facilitated by data collected through an interactive simulation. Findings were evaluated across two distinct environments: transactional networks and transformational networks. The results suggest supply chain leadership and followership both have a significant effect in transactional networks. Interestingly, supply chain followership was discovered to make a greater contribution to overall supply chain structural development and performance than supply chain leadership in transformational environments. The structural model demonstrated good fit and all six hypotheses were at least partially supported

Lean supply chain planning: Simulation of lean techniques integration

Lean Supply Chain (LSC) has become a strategic configuration in order to satisfy customer's expectations efficiently and effectively. LSC concept is the implementation of Lean principles and techniques outside single company boundaries, creating the flow and making SC reacting instead of foreseeing. Supply Chain Planning (SCP) is a part of SCM management strategy that allows managers to align operations of different companies and so improve operations efficiency and effectiveness. Lean Supply Chain Planning (LSCP) is a new SCP model that is growing interest among both academics and practitioners, but it is not well studied yet. This paper aims at providing a theoretical and practical guidelines about Lean techniques implementations impact in SCP. To reach it, a Discret-event-simulation (DES) simulation model of a three-echelon and multi-product supply chain has been set. This research focuses on three principles of Lean production: identifying the value, creating flow to the customer and pull. The results achieved demonstrate that LSCP techniques have a positive impact on inventories levels and in particular, they demonstrate synergy among techniques so that total benefit is greater than the sum of benefits of single technique implementations

Planning and optimising petroleum supply chain

The purpose of this paper is to develop and implement an integrated framework for planning and optimising petroleum supply chain (SC). The framework consists of two stages; first-stage is to address mathematically the strategic planning and the optimisation of the extracted oil which is needed within the petroleum supply chain. While the second stage focuses on the operational planning of the refinery area using a combined discrete and continues simulation modelling techniques. The simulation model considered the following factors: Input Rate, Oil Quality, Distillation Capacity and Number of Failed Separators which are analysed against the performance measures: Total Products and Equipment Utilisation. The results obtained from the experiment are analysed statistically using SPSS Program

Assessing and Mitigating Risk in a Design for Supply Chain Problem

Industry leaders in today's global market strive for continuous improvement in order to remain competitive. One method used by firms for cutting costs and improving efficiency is Design for Supply Chain (DFSC). The objective of this methodology is to design the supply chain in parallel to designing or redesigning a new product. Risk is an inherent element of this DFSC process. Although supply chain risk models and new product development risk models are available, there are few models that consider the combined effect of risk to product development and the supply chain. A gap in the body of knowledge could be filled by a DFSC and risk model that looks at design, supply chain and risk concurrently. This research develops such a model and tests it on two data sets. The most critical risks to incorporate in the model were found through a review of the literature and a survey of industry experts. The model consists of two components. The first component is a Mixed Integer Programming (MIP) model which makes the DFSC decisions while simultaneously considering time-to-market risk, supplier reliability risk and strategic exposure risk. The results from the MIP are then used in the second model component which is a discrete event simulation. The simulation tests the robustness of the MIP solution for supplier capacity risk and demand risk. When a decision maker is potentially facing either of these risks the simulation shows whether it is best to use an alternative solution or proceed with the MIP solution. The model provides analytical results to be used by decision makers, but also allows decision makers to use their own judgment to select the best option for overall profitability. It is shown that the DFSC model with risk is a powerful decision making tool

System dynamics simulation for strategic green supply chain management

The design of appropriate green supply chains in the manufacturing sector is a crucial task. The present paper seeks to (i) identify suitable performance measures for green supply chains and to (ii) develop a dynamic simulation model to assist supply chain decision-makers in developing appropriate policies and strategies in green supply chain management. Based on the principles of the system dynamics methodology, causal linkages between internal and external factors affecting the development of green strategies are investigated. Green concepts are used to develop crucial environmental and eco-efficiency performance measures in regards to strategic green supply management. Results from what-if analysis indicate that proper implementation of green strategies produces significant improvements for environmental, economic/financial and operational performance. Further numerical experiments demonstrate that the model can provide sound managerial insights

The impact of Industry 4.0 implementation on supply chains

Purpose The study aims to analyse the impact of Industry 4.0 implementation on supply chains and develop an implementation framework by considering potential drivers and barriers for the Industry 4.0 paradigm. Design/methodology/approach A critical literature review is performed to explore the key drivers and barriers for Industry 4.0 implementation under four business dimensions: strategic, organisational, technological and legal and ethical. A system dynamics model is later developed to understand the impact of Industry 4.0 implementation on supply chain parameters, by including both the identified driving forces and barriers for this technological transformation. The results of the simulation model are utilised to develop a conceptual model for a successful implementation and acceleration of Industry 4.0 in supply chains. Findings Industry 4.0 is predicted to bring new challenges and opportunities for future supply chains. The study discussed several implementation challenges and proposed a framework for an effective adaption and transition of the Industry 4.0 concept into supply chains. Research limitations/implications The results of the simulation model are utilised to develop a conceptual model for a successful implementation and acceleration of Industry 4.0 in supply chains. Practical implications The study is expected to benefit supply chain managers in understanding the challenges for implementing Industry 4.0 in their network. Originality/value Simulation analysis provides examination of Industry 4.0 adoption in terms of its impact on supply chain performance and allows incorporation of both the drivers and barriers of this technological transformation into the analysis. Besides providing an empirical basis for this relationship, a new conceptual framework is proposed for Industry 4.0 implementation in supply chains

Development model for supply chain network design by demand uncertainty and mode selection

It is necessary to consider the impact of demand uncertainty to model the comprehensive approach for supply chain network design. This paper presents four echelons, multiple commodity, and strategic–tactical model for designing supply chain network. Uncertain demand, transportation mode selection with lead time configuration has been considered. A numerical example has been implemented to verify the applicability of model. Finally, the simulation results and sensitivity analysis confirm that the proposed developed model is a suitable decision framework for designing the supply chain network

Selection of simulation tools for improving supply chain performance

Simulation is an effective method for improving supply chain performance. However, there is limited advice available to assist practitioners in selecting the most appropriate method for a given problem. Much of the advice that does exist relies on custom and practice rather than a rigorous conceptual or empirical analysis. An analysis of the different modelling techniques applied in the supply chain domain was conducted, and the three main approaches to simulation used were identified; these are System Dynamics (SD), Discrete Event Simulation (DES) and Agent Based Modelling (ABM). This research has examined these approaches in two stages. Firstly, a first principles analysis was carried out in order to challenge the received wisdom about their strengths and weaknesses and a series of propositions were developed from this initial analysis. The second stage was to use the case study approach to test these propositions and to provide further empirical evidence to support their comparison. The contributions of this research are both in terms of knowledge and practice. In terms of knowledge, this research is the first holistic cross paradigm comparison of the three main approaches in the supply chain domain. Case studies have involved building ‘back to back’ models of the same supply chain problem using SD and a discrete approach (either DES or ABM). This has led to contributions concerning the limitations of applying SD to operational problem types. SD has also been found to have risks when applied to strategic and policy problems. Discrete methods have been found to have potential for exploring strategic problem types. It has been found that discrete simulation methods can model material and information feedback successfully. Further insights have been gained into the relationship between modelling purpose and modelling approach. In terms of practice, the findings have been summarised in the form of a framework linking modelling purpose, problem characteristics and simulation approach

Sustainable and Dynamic Supply Chain in world Business: Recent Trends

By moving from the "integrated" to the "dynamic" supply chain model, businesses may see their supply chains as flexible ecosystems of people, processes, capital assets, technology, and data. In the rapidly evolving corporate world, effective supply chain management (SCM) is a critical issue. Dynamic SCM necessitates good decision information synchronization and integrated decision-making among autonomous chain partners. Complex supply chains (SCs), which are part of globalised economic systems, must be managed to minimize sustainability-related risks and to manage environmental and social impacts in accordance with the expectations of many stakeholders. The analysis of recent trends has highlighted the fact that use of quantitative modelling techniques for sustainable supply chain management (SSCM) is increasingly becoming more and more popular. Secondly, simulation techniques are underrepresented in SSCM compared to analytical models and mathematical programming. For organizations that are looking to infuse a fresh breath in there SCM operations inclusion of system dynamics (SD) modelling for simulating and analyzing complex and dynamic systems as well as for assisting long-term, strategic decision-making will pay rich dividends.