The boomerang returns? Accounting for the impact of uncertainties on the dynamics of remanufacturing systems

Recent years have witnessed companies abandon traditional open-loop supply chain structures in favour of closed-loop variants, in a bid to mitigate environmental impacts and exploit economic opportunities. Central to the closed-loop paradigm is remanufacturing: the restoration of used products to useful life. While this operational model has huge potential to extend product life-cycles, the collection and recovery processes diminish the effectiveness of existing control mechanisms for open-loop systems. We systematically review the literature in the field of closed-loop supply chain dynamics, which explores the time-varying interactions of material and information flows in the different elements of remanufacturing supply chains. We supplement this with further reviews of what we call the three ‘pillars’ of such systems, i.e. forecasting, collection, and inventory and production control. This provides us with an interdisciplinary lens to investigate how a ‘boomerang’ effect (i.e. sale, consumption, and return processes) impacts on the behaviour of the closed-loop system and to understand how it can be controlled. To facilitate this, we contrast closed-loop supply chain dynamics research to the well-developed research in each pillar; explore how different disciplines have accommodated the supply, process, demand, and control uncertainties; and provide insights for future research on the dynamics of remanufacturing systems

Evolving strategies for single-celled organisms in multi-nutrient environments

When micro-organisms are in environments with multiple nutrients, they often preferentially utilise one first. A second is only utilised once the first is exhausted. Such a two-phase growth pattern is known as diauxic growth. Experimentally, this manifests itself through two distinct exponential growth phases separated by a lag phase of arrested growth. The dura- tion of the lag phase can be quite substantial. From an evolu- tionary point of view the existence of a lag phase is somewhat puzzling because it implies a substantial loss of growth op- portunity. Mutants with shorter lag phases would be prone to outcompete those with longer phases. Yet in nature, diauxic growth with lag phases appears to be a robust phenomenon. We introduce a model of the evolution of diauxic growth that captures the basic interactions regulating it in bacteria. We observe its evolution without a lag phase. We conclude that the lag phase is an adaptation that is only beneficial when fit- ness is averaged over a large number of environments

Verification and Optimization of a PLC Control Schedule

We report on the use of the SPIN model checker for both the verification of a process control program and the derivation of optimal control schedules. This work was carried out as part of a case study for the EC VHS project (Verification of Hybrid Systems), in which the program for a Programmable Logic Controller (PLC) of an experimental chemical plant had to be designed and verified. The intention of our approach was to see how much could be achieved here using the standard model checking environment of SPIN/Promela. As the symbolic calculations of real-time model checkers can be quite expensive it is interesting to try and exploit the efficiency of established non-real-time model checkers like SPIN in those cases where promising work-arounds seem to exist. In our case we handled the relevant real-time properties of the PLC controller using a time-abstraction technique; for the scheduling we implemented in Promela a so-called variable time advance procedure. For this case study these techniques proved sufficient to verify the design of the controller and derive (time-)optimal schedules with reasonable time and space requirements

Statistical discourse analysis: A method for modeling online discussion processes

Online forums (synchronous and asynchronous) offer exciting data opportunities to analyze how people influence one another through their interactions. However, researchers must address several analytic difficulties involving the data (missing values, nested structure [messages within topics], non‐sequential messages), outcome variables (discrete outcomes, rare instances, multiple outcome variables, similarities among nearby messages), and explanatory variables (sequences of explanatory variables, indirect mediation effects, false positives, and robustness of results). We explicate a method that addresses these difficulties (Statistical Discourse Analysis or SDA) and illustrate it on 1,330 asynchronous messages written and selfcoded by 17 students during a 13‐week online educational technology course. Both individual characteristics and message attributes were linked to participants’ online messages. Men wrote more messages about their theories than women did. Moreover, some sequences of messages were more likely to precede other messages. For example, opinions were often followed by elaborations, which were often followed by theorizing

Statistical Discourse Analysis: A method for modeling online discussion processes

Online forums (synchronous and asynchronous) offer exciting data opportunities to analyze how people influence one another through their interactions. However, researchers must address several analytic difficulties involving the data (missing values, nested structure [messages within topics], non‐sequential messages), outcome variables (discrete outcomes, rare instances, multiple outcome variables, similarities among nearby messages), and explanatory variables (sequences of explanatory variables, indirect mediation effects, false positives, and robustness of results). We explicate a method that addresses these difficulties (Statistical Discourse Analysis or SDA) and illustrate it on 1,330 asynchronous messages written and selfcoded by 17 students during a 13‐week online educational technology course. Both individual characteristics and message attributes were linked to participants’ online messages. Men wrote more messages about their theories than women did. Moreover, some sequences of messages were more likely to precede other messages. For example, opinions were often followed by elaborations, which were often followed by theorizing