Using the max-sum algorithm for supply chain emergence in dynamic multiunit environments

Supply chain formation (SCF) is the process of determining the set of participants and exchange relationships within a network with the goal of setting up a supply chain that meets some predefined social objective. Many proposed solutions for the SCF problem rely on centralized computation, which presents a single point of failure and can also lead to problems with scalability. Decentralized techniques that aid supply chain emergence offer a more robust and scalable approach by allowing participants to deliberate between themselves about the structure of the optimal supply chain. Current decentralized supply chain emergence mechanisms are only able to deal with simplistic scenarios in which goods are produced and traded in single units only and without taking into account production capacities or input-output ratios other than 1:1. In this paper, we demonstrate the performance of a graphical inference technique, max-sum loopy belief propagation (LBP), in a complex multiunit unit supply chain emergence scenario which models additional constraints such as production capacities and input-to-output ratios. We also provide results demonstrating the performance of LBP in dynamic environments, where the properties and composition of participants are altered as the algorithm is running. Our results suggest that max-sum LBP produces consistently strong solutions on a variety of network structures in a multiunit problem scenario, and that performance tends not to be affected by on-the-fly changes to the properties or composition of participants.

Life cycle assessment in the food supply chain:a case study

This research aims at assessing the environmental impact of the poultry supply chain from cradle to grave using case study research and also life cycle assessment (LCA). While a limited number of generic poultry production LCA studies have been published, fewer yet assess the whole process of a specific organisation, none comparing the increased impact of further processing. Our results show that irrespectively of the impact assessment method utilised, the process of producing portions is considerably higher in total environmental impact due to the extra raw material required to produce the same mass into retail. Our research contributes to the growing number of LCA studies and could be used by practitioners for comparison against national and international averages. From a theoretical point of view, this research provides new insights into the relationship between vertically integrated supply chains and environmental performance which has not been examined in the past.

Holonic supply chain:a study from family-based manufacturing perspective

In the contemporary business environment, to adhere to the need of the customers, caused the shift from mass production to mass-customization. This necessitates the supply chain (SC) to be effective flexible. The purpose of this paper is to seek flexibility through adoption of family-based dispatching rules under the influence of inventory system implemented at downstream echelons of an industrial supply chain network. We compared the family-based dispatching rules in existing literature under the purview of inventory system and information sharing within a supply chain network. The dispatching rules are compared for Average Flow Time performance, which is averaged over the three product families. The performance is measured using extensive discrete event simulation process. Given the various inventory related operational factors at downstream echelons, the present paper highlights the importance of strategically adopting appropriate family-based dispatching rule at the manufacturing end. In the environment of mass customization, it becomes imperative to adopt the family-based dispatching rule from the system wide SC perspective. This warrants the application of intra as well as inter-echelon information coordination. The holonic paradigm emerges in this research stream, amidst the holistic approach and the vital systemic approach. The present research shows its novelty in triplet. Firstly, it provides leverage to manager to strategically adopting a dispatching rule from the inventory system perspective. Secondly, the findings provide direction for the attenuation of adverse impact accruing from demand amplification (bullwhip effect) in the form of inventory levels by appropriately adopting family-based dispatching rule. Thirdly, the information environment is conceptualized under the paradigm of Koestler's holonic theory.

Detecting EPCIS exceptions in linked traceability streams across supply chain business processes

The EPCIS specification provides an event oriented mechanism to record product movement information across stakeholders in supply chain business processes. Besides enabling the sharing of event-based traceability datasets, track and trace implementations must also be equipped with the capabilities to validate integrity constraints and detect runtime exceptions without compromising the time-to-deliver schedule of the shipping and receiving parties. In this paper we present a methodology for detecting exceptions arising during the processing of EPCIS event datasets. We propose an extension to the EEM ontology for modelling EPCIS exceptions and show how runtime exceptions can be detected and reported. We exemplify and evaluate our approach on an abstraction of pharmaceutical supply chains.

Representing supply chain events on the Web of data

The Electronic Product Code Information Service (EPCIS) is an EPCglobal standard, that aims to bridge the gap between the physical world of RFID1 tagged artifacts, and information systems that enable their tracking and tracing via the Electronic Product Code (EPC). Central to the EPCIS data model are "events" that describe specific occurrences in the supply chain. EPCIS events, recorded and registered against EPC tagged artifacts, encapsulate the "what", "when", "where" and "why" of these artifacts as they flow through the supply chain. In this paper we propose an ontological model for representing EPCIS events on the Web of data. Our model provides a scalable approach for the representation, integration and sharing of EPCIS events as linked data via RESTful interfaces, thereby facilitating interoperability, collaboration and exchange of EPC related data across enterprises on a Web scale.

Advances in decision support systems on the endeavour for supply chain optimality

Industry practitioners are seeking to create optimal logistics networks through more efficient decision-making leading to a shift of power from a centralized position to a more decentralized approach. This has led to researchers, exploring with vigor, the application of agent based modeling (ABM) in supply chains and more recently, its impact on decision-making. This paper investigates reasons for the shift to decentralized decision-making and the impact on supply chains. Effective decentralization of decision-making with ABM and hybrid modeling is investigated, observing the methods and potential of achieving optimality.

Online grocery provision resistance:understanding urban (non-)collaboration and ambiguous supply chain environments

This chapter investigates the resistance by institutional actors in ambiguous supply chain environments for online grocery provision. Recent studies have shown that significant shifts in urban geographies are increasing consumers' expectations of online retail provision. However, at the same time there is also growing evidence that the collaborative practice in online grocery provision within the urban supply chains is resisted. That these trends are found despite growing demand of online provision highlights both the difficulty of bringing geographically dispersed supply partners together and the problems associated with operating within and across ambiguous environments. Drawing upon twenty-nine in-depth interviews with a range of institutional actors, including retail, logistics, and urban planning experts within an urban metropolis in an emerging market, we detail the different ways that collaboration is resisted in online retail provision. Several different patterns of resistance were identified in (non-) collaboration notably, ideological, functional, regulatory and spatial. © 2011, IGI Global. C.

Novel Formulation and Efficient Solution Strategy for Strategic Optimization of an Industrial Chemical Supply Chain Under Demand Uncertainty

This paper is concerned with strategic optimization of a typical industrial chemical supply chain, which involves a material purchase and transportation network, several manufacturing plants with on-site material and product inventories, a product transportation network and several regional markets. In order to address large uncertainties in customer demands at the different regional markets, a novel robust scenario formulation, which has been developed by the authors recently, is tailored and applied for the strategic optimization. Case study results show that the robust scenario formulation works well for this real industrial supply chain system, and it outperforms the deterministic formulation and the classical scenario-based stochastic programming formulation by generating better expected economic performance and solutions that are guaranteed to be feasible for all uncertainty realizations. The robust scenario problem exhibits a decomposable structure that can be taken advantage of by Benders decomposition for efficient solution, so the application of Benders decomposition to the solution of the strategic optimization is also discussed. The case study results show that Benders decomposition can reduce the solution time by almost an order of magnitude when the number of scenarios in the problem is large.

Point-and-shoot: rapid quantitative detection methods for on-site food fraud analysis – moving out of the laboratory and into the food supply chain

Major food adulteration and contamination events occur with alarming regularity and are known to be episodic, with the question being not if but when another large-scale food safety/integrity incident will occur. Indeed, the challenges of maintaining food security are now internationally recognised. The ever increasing scale and complexity of food supply networks can lead to them becoming significantly more vulnerable to fraud and contamination, and potentially dysfunctional. This can make the task of deciding which analytical methods are more suitable to collect and analyse (bio)chemical data within complex food supply chains, at targeted points of vulnerability, that much more challenging. It is evident that those working within and associated with the food industry are seeking rapid, user-friendly methods to detect food fraud and contamination, and rapid/high-throughput screening methods for the analysis of food in general. In addition to being robust and reproducible, these methods should be portable and ideally handheld and/or remote sensor devices, that can be taken to or be positioned on/at-line at points of vulnerability along complex food supply networks and require a minimum amount of background training to acquire information rich data rapidly (ergo point-and-shoot). Here we briefly discuss a range of spectrometry and spectroscopy based approaches, many of which are commercially available, as well as other methods currently under development. We discuss a future perspective of how this range of detection methods in the growing sensor portfolio, along with developments in computational and information sciences such as predictive computing and the Internet of Things, will together form systems- and technology-based approaches that significantly reduce the areas of vulnerability to food crime within food supply chains. As food fraud is a problem of systems and therefore requires systems level solutions and thinking.

Kustannusjohtaminen toimitusketjun hallinnassa

Tämä työ tarkastelee toimitusketjussa käytettyjä kustannusjohtamismenetelmiä. Työn tavoitteena on selvittää mitkä menetelmät ovat useimmiten käytössä ja miten niiden käyttöä on tutkittu kirjallisuudessa. Työ on kirjallisuuskatsaus aiempaan tutkimukseen ja tiedonhaun perusteella pyritään luomaan mahdollisimman laaja kuva tutkituista ja käytössä olevista kustannusjohtamismenetelmistä toimitusketjussa. Työssä tarkasteltuja kustannusjohtamismenetelmiä toimitusketjuissa ovat toimintolaskenta, tavoitekustannuslaskenta, elinkaarikustannuslaskenta ja Balanced Scorecard. Työ esittelee näiden menetelmien teoriat ja tarkastelee niiden käyttötapoja toimitusketjuissa ja tutkittuja käyttökohteita työkaluille. Tutkimus kustannusjohtamismenetelmiin toimitusketjussa on hajanaista. Toimintolaskentaa ja tavoitekustannuslaskentaa on tutkittu laajasti, kun taas elinkaarikustannuslaskennan ja Balanced Scorecardin yleisiä malleja toimitusketjussa on tutkittu vähän ja menetelmien käyttö on tapauskohtaista.

Development and Application of Predictive Models for Survival, Growth, and Death of Enteric Pathogens in Leafy Greens Supply Chain

Leafy greens are essential part of a healthy diet. Because of their health benefits, production and consumption of leafy greens has increased considerably in the U.S. in the last few decades. However, leafy greens are also associated with a large number of foodborne disease outbreaks in the last few years. The overall goal of this dissertation was to use the current knowledge of predictive models and available data to understand the growth, survival, and death of enteric pathogens in leafy greens at pre- and post-harvest levels. Temperature plays a major role in the growth and death of bacteria in foods. A growth-death model was developed for Salmonella and Listeria monocytogenes in leafy greens for varying temperature conditions typically encountered during supply chain. The developed growth-death models were validated using experimental dynamic time-temperature profiles available in the literature. Furthermore, these growth-death models for Salmonella and Listeria monocytogenes and a similar model for E. coli O157:H7 were used to predict the growth of these pathogens in leafy greens during transportation without temperature control. Refrigeration of leafy greens meets the purposes of increasing their shelf-life and mitigating the bacterial growth, but at the same time, storage of foods at lower temperature increases the storage cost. Nonlinear programming was used to optimize the storage temperature of leafy greens during supply chain while minimizing the storage cost and maintaining the desired levels of sensory quality and microbial safety. Most of the outbreaks associated with consumption of leafy greens contaminated with E. coli O157:H7 have occurred during July-November in the U.S. A dynamic system model consisting of subsystems and inputs (soil, irrigation, cattle, wildlife, and rainfall) simulating a farm in a major leafy greens producing area in California was developed. The model was simulated incorporating the events of planting, irrigation, harvesting, ground preparation for the new crop, contamination of soil and plants, and survival of E. coli O157:H7. The predictions of this system model are in agreement with the seasonality of outbreaks. This dissertation utilized the growth, survival, and death models of enteric pathogens in leafy greens during production and supply chain.

From the farm to the fork: fungal occupational exposure in the swine meat supply chain

Feed production, swine and slaughterhouses were already reported as occupational environments with high fungal contamination. This condition can ultimately lead to the development of several health conditions. This study aimed to characterize the occupational exposure to fungal burden in three different settings: swine feed unit, swine units and slaughterhouse.

INTERACTIVE EFFECT OF FIXED TIME ORDER STRATEGIES WITHIN A SUPPLY CHAIN ON ACTUAL IN-STOCK PROBABILITIES

This report mainly deals with the interactive effect of different in-stock probabilities used by every individual in a supply chain. Based on a simulation for 10,000 weeks, the effects of varying in-stock probabilities are observed. Based on these observations, an individual in a supply chain can take counter measures in order to avoid stock out chances hence maintaining profits.