A new data-driven framework to select the optimal replenishment strategy in complex supply chains

- Part of special issue: 10th IFAC Conference on Manufacturing Modelling, Management and Control MIM 2022: Nantes, France, 22-24 June 2022. Edited by Alain Bernard, Alexandre Dolgui, Hichem Haddou Benderbal, Dmitry Ivanov, David Lemoine, Fabio Sgarbossa - Copyright © 2022 The Authors. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/)Motivated by the high variability of markets occurred in the last years, which in turns determined significant uncertainty in lead times and supply chain dynamics, this paper introduces a data-driven framework based on machine learning and metaheuristic optimization to dynamically select the most suitable replenishment strategy for a complex two-echelon (supplier-inventory-factory) supply chain (SC) problem with perishable product and stochastic lead times. Since the supplier dispatches the product (i.e., the raw material) with a fixed expiration date, the product shelf-life strictly depends on the related delivery lead time, which is subject to uncertainty. In addition, a minimum order quantity has to be fulfilled and the time between two consecutive orders cannot be less than one month. The aim of the work is to select the most suitable replenishment strategy able to minimize the average stock level, which is a surrogate cost metric, while respecting a target fill rate. Considering a smoothing order-up-to policy, the data-driven prediction-optimization framework makes use of Artificial Neural Network (ANN) and Particle Swarm Optimization (PSO) to select the best replenishment parameters (i.e., forecasting factor, proportional controller and safety stock factor) able to dynamically enhance the SC economic performance under the fill rate constraint. The ability of the framework under the predictive and the optimization perspective is assessed and a sensitivity analysis on the influence of replenishment parameters is presented as well

Digital transformation of the Portuguese footwear industry

Technology is evolving the fastest it has ever been, and not following innovation can be life-threatening for any company. The Fourth Industrial Revolution is based on interconnection, transparency, and decentralization to achieve smart factories. Using Industry 4.0 technological pillars is essential to transforming industrial production, increasing productivity, efficiency, and quality while reducing costs and waste. The footwear industry has significant importance in the Portuguese economy. As part of the fashion industry, it is expected to innovate and create trends while maintaining classiness and timelessness, making it unique and complex. Furthermore, since Industry 4.0 is a currently highly studied and talked-about topic, it only makes sense to understand the adoption state of Industry 4.0 technology in such a complex industry as the Portuguese footwear industry. The study used qualitative exploratory research, collecting insight from footwear companies and the sector associations, through direct observations, via shopfloor visits, and semi-structured interviews, where key participants discussed the level of Industry 4.0 implementation. Despite having motivation, there is a long way to go. Although some of the technologies of Industry 4.0 are heavily utilized, such as simulation and horizontal and vertical integration, companies need more Industry 4.0 literacy to move towards an integral and effective implementation. A cluster composed mainly of microenterprises, paired with strong resistance to change and where the handmade aspect is valued, hinders the adoption of Industry 4.0. Although changing slowly, it is an industry with the potential to participate in Industry 4.0.A tecnologia está a evoluir mais rápido do que nunca, e não acompanhar a inovação pode ser um risco de vida para qualquer empresa. A Quarta Revolução Industrial baseia-se na interconexão, transparência e descentralização com o objetivo de alcançar fábricas inteligentes. A utilização dos pilares tecnológicos da Indústria 4.0 é essencial para transformar a produção industrial, aumentando a produtividade, a eficiência e a qualidade, reduzindo custos e desperdícios. A indústria do calçado tem uma importância significativa na economia portuguesa. Como parte da indústria da moda, espera-se que inove e crie tendências, mantendo a classe e a intemporalidade, tornando-a única e complexa. Além disso, sendo a Indústria 4.0 um tema atualmente muito estudado e falado, faz sentido perceber o estado de adoção da tecnologia da Indústria 4.0 numa indústria tão complexa como a indústria portuguesa de calçado. O estudo recorreu a uma investigação qualitativa exploratória, recolhendo informação junto das empresas de calçado e das associações do setor, através de observações diretas, via visitas ao chão de fábrica, e entrevistas semiestruturadas, onde os participantes foram questionados sobre Indústria 4.0. Apesar da motivação, há um longo caminho a percorrer. Embora algumas tecnologias da Indústria 4.0 sejam fortemente utilizadas, como simulação e integração horizontal e vertical, as empresas precisam de mais conhecimento de Indústria 4.0, para uma implementação integral e eficaz. Um cluster composto principalmente por microempresas, aliado a uma forte resistência à mudança e onde o aspecto artesanal é valorizado, dificulta a adoção da Indústria 4.0. Apesar da lenta mudança, é uma indústria com potencial para participar na Indústria 4.0

Information visibility and its effect on supply chain dynamics

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2000.Includes bibliographical references (p. 61-64).Supply chains are nonlinear dynamic systems, the control of which is complicated by long, variable delays in product and information flows. In this thesis, we present a novel framework for improving the visibility of information in supply chains by reducing the delays in information flow. We first analyze the growth and evolution of production and operations management software over the past three decades, and the current trends in their development, coupled with recent advances in radio frequency technology, wireless communications, data representation methods, and the internet. Information visibility is identified as one of the key elements for successful implementation of any such software. We analyze the dynamics of a supply chain under different scenarios of information visibility and forecasting decisions with the help of simulations. Possible improvements in supply chain costs are identified, provided information visibility. We propose a framework to achieve information visibility in the supply chain using radio frequency tags, tag readers, product identification codes, an object description language, and the internet.by Yogesh V. Joshi.S.M

A Relative Comparison of Leading Supply Chain Management Software Packages

Supply Chain Management (SCM) has proven to be an effective tool that aids companies in the development of competitive advantages. SCM Systems are relied on to manage warehouses, transportation, trade logistics and various other issues concerning the coordinated movement of products and services from suppliers to customers. Although in today’s fast paced business environment, numerous supply chain solution tools are readily available to companies, choosing the right SCM software is not an easy task. The complexity of SCM systems creates a multifaceted issue when selecting the right software, particularly in light of the speed at which technology evolves. In this paper, we use the approach of Analytic Hierarchy Process (AHP) to determine which SCM software best meets the needs of a company. The AHP approach outlined in this paper can be easily transferred to the comparison of other SCM software packages

Achieving manufacturing excellence through the integration of enterprise systems and simulation

This paper discusses the significance of the enterprise systems and simulation integration in improving shop floor’s short-term production planning capability. The ultimate objectives are to identify the integration protocols, optimisation parameters and critical design artefacts, thereby identifying key ‘ingredients’ that help in setting out a future research agenda in pursuit of optimum decision-making at the shop floor level. While the integration of enterprise systems and simulation gains a widespread agreement within the existing work, the optimality, scalability and flexibility of the schedules remained unanswered. Furthermore, there seems to be no commonality or pattern as to how many core modules are required to enable such a flexible and scalable integration. Nevertheless, the objective of such integration remains clear, i.e. to achieve an optimum total production time, lead time, cycle time, production release rates and cost. The issues presently faced by existing enterprise systems (ES), if properly addressed, can contribute to the achievement of manufacturing excellence and can help identify the building blocks for the software architectural platform enabling the integration

Organizational, systems and human issues in production planning, scheduling and control

With global markets and global competition, pressures are placed on manufacturing organizations to compress order fulfillment times, meet delivery commitments consistently and also maintain efficiency in operations to address cost issues. This chapter argues for a process perspective on planning, scheduling and control that integrates organizational planning structures, information systems as well as human decision makers. The chapter begins with a reconsideration of the gap between theory and practice, in particular for classical scheduling theory and hierarchical production planning and control. A number of the key studies of industrial practice are then described and their implications noted. A recent model of scheduling practice derived from a detailed study of real businesses is described. Socio-technical concepts are then introduced and their implications for the design and management of planning, scheduling and control systems are discussed. The implications of adopting a process perspective are noted along with insights from knowledge management. An overview is presented of a methodology for the (re-)design of planning, scheduling and control systems that integrates organizational, system and human perspectives. The most important messages from the chapter are then summarized

Organizational, systems and human issues in production planning, scheduling and control

With global markets and global competition, pressures are placed on manufacturing organizations to compress order fulfillment times, meet delivery commitments consistently and also maintain efficiency in operations to address cost issues. This chapter argues for a process perspective on planning, scheduling and control that integrates organizational planning structures, information systems as well as human decision makers. The chapter begins with a reconsideration of the gap between theory and practice, in particular for classical scheduling theory and hierarchical production planning and control. A number of the key studies of industrial practice are then described and their implications noted. A recent model of scheduling practice derived from a detailed study of real businesses is described. Socio-technical concepts are then introduced and their implications for the design and management of planning, scheduling and control systems are discussed. The implications of adopting a process perspective are noted along with insights from knowledge management. An overview is presented of a methodology for the (re-)design of planning, scheduling and control systems that integrates organizational, system and human perspectives. The most important messages from the chapter are then summarized

An enhanced framework for blood supply chain risk management

A blood supply chain (BSC) is a very long and complex sequence of processes heavily sequential. If one of them is executed in an incorrect way and this error is not detected, it leads to an incorrect transfusion outcome, that could seriously affect patients. For this reason, there is a strong need to identify and prevent adverse events along the entire BSC, in order to reduce their probability of occurrence. This also helps improving BSC sustainability from both the environmental and the social perspectives. The paper extends an existing healthcare supply chain risk management framework already applied to the blood transfusion process to address multiple BSC echelons and identify the cause and effect relationships among the adverse events that might occur. To this end, Fault Tree Analysis is added to the risk management tools part of the original framework as well as Key Performance Indicators are applied to detect risky event manifestation. The first application of the proposed approach to a blood bank and a hospital ward revealed its effectiveness in identifying the BSC activities most subjected to risk. Also, connections between adverse events and causal relationships among their sources were found, leading to understanding whether an adverse event is caused by a risk source in the same echelon where it occurs or by the concurrent manifestation of several adverse events upstream in the BSC. Future research will be devoted to numerically evaluate probability of occurrence and impact of risky events as well as integrating the framework with a classification of criticalities based on their severity

A Managerial Analysis of Urban Parcel Delivery: A Lean Business Approach

The improper integration of traditional transportation modes with low emissions vehicles can generate a price war that reduces the service quality, undermining the efficiency and the profitability of parcel delivery operators. This paper aims to provide managerial insights to design a win-win strategy for the co-existence of traditional and green business models. In doing so, we adopt a multi-disciplinary approach that integrates a qualitative analysis through a Lean Business methodology, named GUEST, with a quantitative analysis based on simulation-optimisation techniques. This kind of holistic vision has received little attention in the literature. The first analysis investigates the parcel delivery industry with an emphasis on the main business models involved, their costs and revenues structures, while the quantitative part aims to simulate the system and extract sustainable policies. In particular, results highlight that in deploying mixed-fleet policies, the decision-makers have to focus both on the environmental sustainability that benefits from the adoption of low-emission vehicles, and on the operational feasibility and economic sustainability of the two services. In this direction, the paper suggests some managerial insights concerning the split of the customer demand between traditional and green operators, according to the classes of parcels and geographical areas of the city

Order batching and picking optimization in terms of supply chain management (SCM)

In distribution center (DC), at the time of forming a batch, by considering the order holding time and picking time in the system, an algorithm based on the first-come, first served based (FCFS) rule is presented. In the proposed algorithm, both order picking factor and order holding factor are used in order to reflect the throughput of the system and response of orders.;Furthermore, some simple batching policies for considering the order holding time in the system are presented. They may result in meeting its customers\u27 requirements for larger numbers of smaller orders and rapid turnaround. They reflect the well-known supply chain management (SCM) concept by taking the customer\u27s need into consideration. Their performance measure of order response time that consists of order picking time and order holding time is evaluated and compared.;Finally, this thesis also develops a new optimization-based joint order batching and picking framework for warehousing and distribution systems. The nested partitions (NP) method that integrates global sampling of the feasible region and local search heuristic is applied to this problem. To speed up the computation, the improved NP-algorithm is developed. Also, by taking the special structure of the problem in account, an improved NP method in terms of small computational time is developed