Sustainable development of global supply chains—part 1: sustainability optimization framework

In global industry supply chains, environmental sustainability optimization addresses the overall consumption of resources and energy, the reduction of carbon emissions and generated waste to name a few. In this paper, we propose a holistic sustainability optimization framework for strategic network design of industry supply chains under consideration of economic, social as well as ecologic objectives. The framework is flexible to incorporate multiple sustainability indicators, alternative sustainability optimization strategies as well as a variety of internal and external industry-specific factors which impact the sustainability of the entire industry supply chain in the long-term. The core of the framework is an end-to-end closed-loop value chain model consisting of process, transport and product-in-use modules. For the first time, the product-in-use impact (“use” vs. “make”) is integrated in one network design approach. In addition, the model fully closes the loop from sourcing of raw materials via manufacturing towards reverse value chain steps such as disposal and recycling. Finally, we propose the minimize-time-to-sustainability approach as new optimization strategy for long-term network design problems focusing on minimizing the time, industry supply chain structures need to transform into sustainability steady states for all defined sustainability indicators such as CO₂e emissions, costs or social indicators based on defined target values. In part 2 of this paper the application of the optimization framework to the European automotive industry is shown.     

Sustainable development of global supply chains—part 2: investigation of the European automotive industry

In global industry supply chains, environmental sustainability optimization addresses the overall consumption of resources and energy, the reduction of carbon emissions and generated waste to name a few. In the second part of this paper, we apply the sustainability optimization framework developed in part 1 to the European automotive industry supply chain. Numerical experiments based on empirical industry data show the impact of optimization strategies on overall costs and emissions in the industry and the possible long-term development of the industry supply chain including the relocation of production capacities, the choice of transportation modes and the potential change towards lower emission products such as electric vehicles. In addition we demonstrate how the novel optimization strategy of minimizing the time-to-sustainability is applied and how it creates transparency of the feasibility of different sustainability targets, e.g. reduction targets for greenhouse gas emissions. Specifically, the minimum time is determined the industry would need to achieve the pre-defined targets. Related optimization results create new insights and provide decision support for policymakers and industry in developing sustainability strategies and specific targets.     

A two-stage sequential planning scheme for integrated operations planning and scheduling system using MILP: the case of an engine assembler

This paper presents an operations planning scheme based on mathematical programming models (specifically, Mixed-Integer Linear Programming (MILP) models) integrated into a web-enabled Advanced Planning and Scheduling System (APS), developed for and implemented in an engine assembler that supplies the car industry. One objective of this paper is to provide empirical insights into some operations planning characteristics in the automotive industry. The other main objective is to show MILP models and their use to create plans that enable the coordination of different planning levels (mid-term and short-term) and planning domains (procurement, production and distribution). The APS fulfills the requirements of an engine assembler in the automotive sector (namely lean-type constraints and objectives). The system is based on two MILP models, which have been purposely developed together along with their relations. The models presented herein provide a solution that considers supply chain objectives and constraints, and are integrated by means of data and constraints which have proven sufficient to fulfill users?? and stakeholders?? requirements. This case study presents the models?? most relevant aspects and their implementation.     

An industry survey of implementation strategies for clinical supply chain management of cell and gene therapies

Background aimsThe novelty of cell and gene therapies (CGTs) has introduced unique supply chain challenges and considerations not seen by chemically synthesized (small-molecule) drugs. These complexities increase during the clinical phases, where drug safety and efficacy milestones are still underdeveloped. For example, for autologous therapies such as chimeric antigen receptor T-cell therapies, in which the treatment is developed from the patient's own cells, supply chain management plays an integral role in chemistry, manufacturing and control processes. Supply chain management requires proactive planning because of the strict cold chain requirements and time sensitivity of CGTs. This research examines strategies and responses to challenges experienced by industry stakeholders (e.g., sponsors and manufacturers) during the implementation phases of clinical supply chain management. This research further evaluates the adequacy of the current regulatory framework for distribution and supply chain management of CGTs in the US.MethodsA survey methodology was used to query subject matter experts from the biopharmaceutical industry who were familiar with the clinical supply management of CGTs in the US. The survey instrument was developed using an implementation framework and disseminated electronically to mid- and senior-level subject matter experts who had experience with clinical trials, supply chain management and CGTs.ResultsA total of 128 respondents accessed the survey, and 105 respondents answered at least one question. Seventy-five respondents completed the survey. Results showed that a lack of harmonization in regulations across the supply chain, limited resources, challenges with vendor management, high costs and complexities in the supply chain due to product specificity and customization proved to be impediments for the industry. In addition, the coronavirus disease 2019 pandemic had a significant impact on supply chain implementation. The results revealed that less than half of the respondents had business continuity plans in place. These challenges increased for smaller and mid-size organizations. Thirty percent of small and mid-size organizations were less prepared to scale up than larger companies.ConclusionsSuggestions from industry stakeholders were to adopt and enforce Good Distribution Practices in the US (81%), pre-plan distribution strategies with internal and external stakeholders along the supply chain and develop agile systems and robust processes end to end. Hurdles in scaling up and scaling out from the clinical to commercial phases for time- and temperature-sensitive CGT products make it difficult to predict the supply chain's long-term feasibility. Although there are initiatives to improve these impediments, such as improving industry partnerships and creating global CGT transportation standards, there are still regulatory knowledge gaps present for CGTs. Therefore, it is essential to establish a baseline and foundation for CGT supply chains extending beyond the loading dock.     

Managing perishability in production-distribution planning: a discussion and review

Managing perishability may represent a remarkable problem in supply chain management of a varied set of industries. In fact, perishability can influence, for example, productivity or customer service and it may happen to occur in one or more processes throughout the supply chain. In this paper a review on planning models that handle perishability issues in production and distribution is conducted. The contribution of this paper is three-fold. First, a new framework for classifying perishability models based on multiple process features is presented. Second, it draws the community attention to the importance of managing perishability in many different industries’ supply chains by showing its relevance and by reviewing the literature related to production and distribution planning. Finally, it points towards research opportunities so far not addressed by the research community in this challenging field.     

Manufacturing capacity planning and the value of multi-stage stochastic programming under Markovian demand

Capacity planning is a crucial part of global manufacturing strategies in the automotive industry, especially in the presence of volatile markets with high demand uncertainty. Capacity adjustments in machining intensive areas, e.g. body shop, paint shop, or aggregate machining face lead times exceeding a year, making an elaborated decision support indispensable. In this regard, two-stage stochastic programming is a frequently used framework to support capacity and flexibility decisions under uncertainty. However, it does not anticipate future capacity adjustment opportunities in response to market demand developments. Motivated by empirical findings from the automotive industry, we develop a multi-stage stochastic dynamic programming approach where the evolution of demand is represented by a Markov demand model. An efficient multi-stage solution algorithm is proposed and the benefits compared to a rolling horizon application of a two-stage approach are illustrated for different generic manufacturing networks. Especially network structures with limited flexibility might significantly benefit from applying a multi-stage framework.     

A multiscale simulation framework for the manufacturing facility and supply chain of autologous cell therapies

Background aimsAutologous cell therapy (AuCT) is an emerging therapeutic treatment that is undergoing transformation from laboratory- to industry-scale manufacturing with recent regulatory approvals. Various challenges facing the complex AuCT manufacturing and supply chain process hinder the scale out and broader application of this highly potent treatment.MethodsWe present a multiscale logistics simulation framework, AuCT-Sim, that integrates novel supply chain system modeling algorithms, methods, and tools. AuCT-Sim includes a single facility model and a system-wide network model. Unique challenges of the AuCT industry are analyzed and addressed in AuCT-Sim. Decision-supporting tools can be developed based on this framework to explore “what-if” manufacturing and supply chain scenarios of importance to various cell therapy stakeholder groups.ResultsTwo case studies demonstrate the decision-supporting capability of AuCT-Sim where one investigates the optimal reagent base stocking level, and the other one simulates a reagent supply disruption event. These case studies serve as guidelines for designing computational experiments with AuCT-Sim to solve specific problems in AuCT manufacturing and supply chain.DiscussionThis simulation framework will be useful in understanding the impact of possible manufacturing and supply chain strategies, policies, regulations, and standards informing strategies to increase patient access to AuCT.     

Delivery mode planning for distribution to brick-and-mortar retail stores: discussion and literature review

In the retail industry, there are multiple products flowing from different distribution centers to brick-and-mortar stores with distinct characteristics. This industry has been suffering radical changes along the years and new market dynamics are making distribution more and more challenging. Consequently, there is a pressure to reduce shipment sizes and increase the delivery frequency. In such a context, defining the most efficient way to supply each store is a critical task. However, the supply chain planning decision that tackles this type of problem, delivery mode planning, is not well defined in the literature. This paper proposes a definition for delivery mode planning and analyzes multiple ways retailers can efficiently supply their brick-and-mortar stores from their distribution centers. The literature addressing this planning problem is reviewed and the main interdependencies with other supply chain planning decisions are discussed.     

Putting Your Money Where Your Mouth Is: Why Sustainability Reporting Based on the Triple Bottom Line Can Be Misleading

In the packaged food industry, Corporate Social Responsibility (CSR) is an informal requirement for which firms account through sustainability reporting. CSR behaviors are often reported and analyzed using the Triple Bottom Line (3BL) framework, which categorizes them as affecting people, planet, or profit. 3BL is useful in determining which of these categories is most elaborated upon by the firm, but has a limited scope and many documented criticisms. This paper aims to address the aforementioned insufficiencies by augmenting the 3BL framework with two important attributes of CSR practices: (1) the presence of change in core firm behavior of the firm itself or of others in the supply chain, and (2) whether the behavior qualifies as being outside of the firm’s normal business practice or is something that they might have done anyway. We qualitatively analyze CSR behaviors described in sustainability reports and interviews from major players in the packaged food industry and categorize them using these attributes as a supplement to 3BL. This enables us to separate the behaviors from their framing and analyze them more critically. Our results demonstrate how the visible CSR efforts of a firm can be misleading at first glance. Using only 3BL, we find that the CSR focus of firms in this industry is people. We then discover that the codes focusing on people (as opposed to planet or profit) require the least amount of real structural change from a firm or its supply chain partners, and thus arguably, the least amount of effort. We also find that behaviors that focus on planet require the most effort within the firm itself, but for behaviors involving supply chain partners, effort is required for behaviors in all three categories. Finally, we find that CSR behavior that is related to planet tends to go beyond normal business practice.     

Race and reputation: perceived racial group trustworthiness influences the neural correlates of trust decisions

Decisions to trust people with whom we have no personal history can be based on their social reputation-a product of what we can observe about them (their appearance, social group membership, etc.)-and our own beliefs. The striatum and amygdala have been identified as regions of the brain involved in trust decisions and trustworthiness estimation, respectively. However, it is unknown whether social reputation based on group membership modulates the involvement of these regions during trust decisions. To investigate this, we examined blood-oxygenation-level-dependent (BOLD) activity while participants completed a series of single-shot trust game interactions with real partners of varying races. At the time of choice, baseline BOLD responses in the striatum correlated with individuals' trust bias-that is, the overall disparity in decisions to trust Black versus White partners. BOLD signal in the striatum was higher when deciding to trust partners from the race group that the individual participant considered less trustworthy overall. In contrast, activation of the amygdala showed greater BOLD responses to Black versus White partners that scaled with the amount invested. These results suggest that the amygdala may represent emotionally relevant social group information as a subset of the general detection function it serves, whereas the striatum is involved in representing race-based reputations that shape trust decisions.     

Economic Profits Enhance Trust,Perceived Integrity and Memory of Fairness in Interpersonal Judgment

Does money lead to trust in personality and intention of others? Humans have a strong tendency to judge the intention of others from their sequent behaviors. In general, people trust others who behave fairly, but not always. Here we show that judgments of both intentional aspects and memory of intentional behavior are automatically influenced by unintentional benefits from the behaviors of others. We conducted a reward-manipulated and repeated trust game by using real participants interacting with moving image partners on a computer screen. The participants assessed likability, trustworthiness, and perceived integrity of the partners in pre- and post-game questionnaires. The results of judgments of all three dimensions and the memory of frequency of each partner''s fair behavior (sharing) were strongly influenced by profitability in the trust game, even though all partners shared 75% of the profit and participants were told that profitability was randomly assigned to each partner. Furthermore, these effects were moderated by the gender of the participants: males were more sensitive to monetary profits than were females. The results reveal that humans automatically trust, approve the integrity of, and recall well the fair behavior of others who provide affectively positive outcomes such as monetary profits. We call this phenomenon the “affect ripple effect”.     

Coexistence Opportunities for Coal Seam Gas and Agribusiness

Australia's prospects to become a key energy exporter in the Asia‐Pacific region has driven rapid development and expansion of its coal seam gas (CSG) industry, particularly in regional Queensland, Australia. The vast majority of Australia's current CSG developments and reserves are situated in agriculture‐rich, cattle‐grazing regions; therefore, it is critical to identify symbiotic relationships between agri‐based industries and the CSG industry to achieve beneficial coexistence. The CSG industry has generated infrastructure such as gas and water pipelines, water storage and treatment facilities, transportation and electricity networks, and other CSG‐associated services (e.g., accommodation, education, and medical facilities), which have the potential to improve regional communities and facilitate economic growth. This article aims to investigate these coexistence opportunities, including the use of by‐products (mainly water produced during CSG extraction), infrastructure, and services generated from the CSG industry, which can provide value to the local industries. Focusing on the cattle value chain, the authors suggest an agri‐based industrial coexistence model that indicates material‐water flows and optimized utilization of infrastructure that not only promote coexistence between the agribusiness and CSG industries, but expand the cattle value‐chain productivity in rural Queensland. A water balance has been conducted around the suggested coexistence model with the aim of quantifying water flows, to indicate the supply versus demand scenario associated with CSG‐sourced water production. The results of the water balance indicate that CSG water supply has the potential to meet the requirements of agribusiness promoting industries.     

STACRP: a secure trusted auction oriented clustering based routing protocol for MANET

In mobile ad hoc network?(MANET) nodes have a tendency to drop others’ packet to conserve its own energy. If most of the nodes in a network start to behave in this way, either a portion of the network would be isolated or total network functionality would be hampered. This behavior is known as selfishness. Therefore, selfishness mitigation and enforcing cooperation between nodes is very important to increase the availability of nodes and overall throughput and to achieve the robustness of the network. Both credit and reputation based mechanisms are used to attract nodes to forward others’ packets. In light of this, we propose a game theoretic routing model, Secure Trusted Auction oriented Clustering based Routing Protocol (STACRP), to provide trusted framework for MANET. Two auction mechanisms procurement and Dutch are used to determine the forwarding cost-per-hop for intermediate nodes. Our model is lightweight in terms of computational and communication requirements, yet powerful in terms of flexibility in managing trust between nodes of heterogeneous deployments. It manages trust locally with minimal overhead in terms of extra messages. STACRP organizes the network into 1-hop disjoint clusters and elects the most qualified and trustworthy nodes as Clusterhead. The trust is quantified with carefully chosen parameters having deep impact on network functionality. The trust model is analyzed using Markov chain and is proven as continuous time Markov chain. The security analysis of the model is analyzed to guarantee that the proposed approach achieves a secure reliable routing solution for MANETs. The proposed model have been evaluated with a set of simulations that show STACRP detects selfish nodes and enforces cooperation between nodes and achieves better throughput and packet delivery ratio with lees routing overhead compare to AODV.     

Simulation and analysis for sustainable product development

Purpose

Simulation plays a critical role in the design of products, materials, and manufacturing processes. However, there are gaps in the simulation tools used by industry to provide reliable results from which effective decisions can be made about environmental impacts at different stages of product life cycle. A holistic and systems approach to predicting impacts via sustainable manufacturing planning and simulation (SMPS) is presented in an effort to incorporate sustainability aspects across a product life cycle.

Methods

Increasingly, simulation is replacing physical tests to ensure product reliability and quality, thereby facilitating steady reductions in design and manufacturing cycles. For SMPS, we propose to extend an earlier framework developed in the Systems Integration for Manufacturing Applications (SIMA) program at the National Institute of Standards and Technology. SMPS framework has four phases, viz. design product, engineer manufacturing, engineer production system, and produce products. Each phase has its inputs, outputs, phase level activities, and sustainability-related data, metrics and tools.

Results and discussion

An automotive manufacturing scenario that highlights the potential of utilizing SMPS framework to facilitate decision making across different phases of product life cycle is presented. Various research opportunities are discussed for the SMPS framework and corresponding information models.

Conclusions

The SMPS framework built on the SIMA model has potential in aiding sustainable product development.     

Towards a harmonised framework methodology for the environmental assessment of food and drink products

Introduction

??Food and drink?? products are the basis of life. However, it is recognised that their supply also contributes to the environmental impacts associated with production and consumption. Recently, an increasing number of food chain partners and public authorities have introduced a widening range of initiatives to provide information about the environmental performance of food and drink products. These initiatives show a high degree of diversity in terms of their chosen scope, assessment methodologies and means of communication, which has the potential to confuse or even mislead consumers and other stakeholders. In this context, the European Food Sustainable Consumption and Production (SCP) Round Table was launched by food supply chain partners and the European Commission with the vision of promoting a science-based, coherent approach to sustainable consumption and production in the European food sector.

Objectives

This article presents this European initiative by introducing its Guiding Principles and summarizing the proceedings of the scientific workshop held in Ispra on 14?C15 June 2010. The aim of the workshop was to identify scientific inputs for developing the harmonised framework methodology for assessing the environmental issues of food and drink products. In this context, the main purpose was to provide a common understanding of what is involved in reliable and robust environmental assessments of the food chain, current limitations, and how to go from detailed assessments to more focused criteria, guidance and tools.

Conclusion

The current experiences presented in the workshop demonstrate that much advancement has already been made towards the measurement and management of the environmental performance of food and drink products. Detailed methodologies and tools are already being used by various players. According to the workshop speakers, the definition of methodological choices concerning the functional unit, system boundaries, cut-off criteria, allocation rules and environmental impact categories are some of the key issues to be fixed in the harmonised framework methodology. The Round Table process has the potential to make a substantial contribution to the sustainable consumption and production of food and drink products. This model might be proposed and reiterated for other sectors as well.     

A network approach for modeling and design of agile supply chains using a flexibility construct

Agility can be viewed as a need to encourage the enterprise-wide integration of flexible and core competent resources so as to offer value-added product and services in a volatile competitive environment. Since flexibility is considered a property that provides change capabilities of different enterprise-wide resources and processes in time and cost dimensions, supply chain flexibility can be considered a composite state to enterprise-wide resources to meet agility needs. Enterprise modeling frameworks depicting these composite flexibility states are difficult to model because of the complex and tacit interrelationship among system parameters and also because agility thrives on many business objectives. In view of this, the modeling framework presented in this paper is based on analytical network process (ANP) since this methodology can accommodate the complex and tacit interrelationship among factors affecting enterprise agility. The modeling framework forms a three-level network with the goal of attaining agility from the perspective of market, product, and customer as the actors. The goal depends on substrategies that address the characteristics of the three actors. Each of these substrategies further depends on manufacturing, logistic, sourcing, and information technology (IT) flexibility elements of the enterprise supply chain (SC). The research highlights that, under different environmental conditions, enterprises require synergy among appropriate supply chain flexibilities for practising agility. In the present research, the ANP modeling software tool Super Decisions? has been used for relative prioritization of the supply chain flexibilities. We demonstrate through sensitivity analysis that dynamic conditions do require adjustments in the enterprise-wide flexibility spectrum.     

Multi-scale modeling for sustainable chemical production

With recent advances in metabolic engineering, it is now technically possible to produce a wide portfolio of existing petrochemical products from biomass feedstock. In recent years, a number of modeling approaches have been developed to support the engineering and decision-making processes associated with the development and implementation of a sustainable biochemical industry. The temporal and spatial scales of modeling approaches for sustainable chemical production vary greatly, ranging from metabolic models that aid the design of fermentative microbial strains to material and monetary flow models that explore the ecological impacts of all economic activities. Research efforts that attempt to connect the models at different scales have been limited. Here, we review a number of existing modeling approaches and their applications at the scales of metabolism, bioreactor, overall process, chemical industry, economy, and ecosystem. In addition, we propose a multi-scale approach for integrating the existing models into a cohesive framework. The major benefit of this proposed framework is that the design and decision-making at each scale can be informed, guided, and constrained by simulations and predictions at every other scale. In addition, the development of this multi-scale framework would promote cohesive collaborations across multiple traditionally disconnected modeling disciplines to achieve sustainable chemical production.     

英国国家植物生物安全治理路径研究

植物病虫疫情是全球粮食生产安全的重大威胁。英国较重视植物安全治理,较早开始布局相关政策,构建风险防控体系,取得了良好成效。本文采用文献调研、分析与综合、比较研究等方法,围绕英国面临的植物安全的严峻形势,分析了英国在战略规划、治理体系、制度建设、技术研发、国际合作等方面的经验与做法。英国政府把植物生物安全纳入国家安全战略,统筹植物生物安全组织体系,制定国际先进水平的安全制度,构建有生物安全保障的植物供应链,推进产学研深度融合,大力开展全民科学,对我国生物安全建设具有重要借鉴意义。纵观英国植物生物安全治理体系建设的做法,本文对我国植物生物安全体系建设提出了相应建议,以期为相关领域研究者和政策制定者提供参考。     

Operational flexibility quantification in a make-to-order assembly system

Manufacturing flexibility is becoming a fundamental production objective, along with cost, quality, and delivery time. Current production systems face quick changes in market conditions and they need to adapt in this environment. The supply chain and industrial globalization give an important role for assembly systems. Placed at the end of the value chain, assembly systems must face those quick changes successfully to reach the expected performance. The key performance indicators are normally based on cost, quality, and delivery time objectives. Reducing costs and improving quality are almost universal goals. Delivery time is typically determined by customer demand in the supply chain, planning from make-to-stock to make-to-order, and aspiring to reach a just-in-time manufacturing system. In this context, flexibility could be the differential advantage to tackle uncertainty. Closely related to the rest of production objectives and the overall performance of the system, flexibility must be integrated in the system for successful decision-making in operations. This work presents this approach of flexibility. A brief review of flexibility concepts and measurements in the literature precedes an introduction to flexibility, defined based on the function of utility. This function represents the expectations of system performance. This approach allows the formulation of the taxonomy of operational flexibility in agreement with the classical types identified in former works. Next, an integer model is programmed to simulate the basic behavior of task planning in a make-to-order assembly system. This first application illustrates flexibility quantification based on utility evolution. The use of common industrial parameters to quantify operational flexibility will finally facilitate an integrated interpretation of system performance trends.     

Redesigning the Industrial Ecology of the Automobile

This article explores the potential of industrial ecology to inform the redesign of an existing industry: that which is concerned with the production, sale, and support of automobiles. In so doing, it brings together the concepts embedded in industrial ecology with issues of economic scale, product design or technology, process technology, and the way in which new combinations of these features can result in an alternative structure for the automotive industry that has the potential to enhance sustainability performance. In so doing, the article advances the general argument that the economic, technical, and spatial organization of production and consumption are co-determined in a manner that collectively shapes the industrial ecology of an industry. In contradistinction to the prevailing industry, the article then advances the concept of micro factory retailing as an alternative framework for the industry that would result in significantly different performance in terms of industrial ecology.