Effect of reconfiguration costs on planning for capacity scalability in reconfigurable manufacturing systems

In a globally competitive market for products, manufacturers are faced with an increasing need to improve their flexibility, reliability, and responsiveness to meet the demands of their customers. Reconfigurable manufacturing systems (RMS) have become an important manufacturing paradigm, because they broadly encompass the ability to react efficiently to this environment by providing the exact capacity and functionality needed when needed. This paper studies how such new systems can manage their capacity scalability planning in a cost effective manner. An approach for modeling capacity scalability planning is proposed. The development of the model is based on set theory and the regeneration point theorem which is mapped to the reconfigurable manufacturing paradigm as the capacity scalability points of that system. The cost function of the model incorporates both the physical capacity cost based on capacity size and costs associated with the reconfiguration process which referred to as the scalability penalty cost and scalability effort cost. A dynamic programming (DP) approach is manipulated for the development of optimal capacity scalability plans. The effect of the reconfiguration costs on the capacity scalability planning horizon and overall cost is investigated. The results showed the relation between deciding on the optimal capacity scalability planning horizon and the different reconfiguration costs. Results also highlighted the fact that decreasing costs of reconfiguration will lead to cost effective implementation of reconfigurable manufacturing systems.     

Impacts of Biotic Resource Enrichment on a Predator–Prey Population

The environmental carrying capacity is usually assumed to be fixed quantity in the classical predator–prey population growth models. However, this assumption is not realistic as the environment generally varies with time. In a bid for greater realism, functional forms of carrying capacities have been widely applied to describe varying environments. Modelling carrying capacity as a state variable serves as another approach to capture the dynamical behavior between population and its environment. The proposed modified predator–prey model is based on the ratio-dependent models that have been utilized in the study of food chains. Using a simple non-linear system, the proposed model can be linked to an intra-guild predation model in which predator and prey share the same resource. Distinct from other models, we formulate the carrying capacity proportional to a biotic resource and both predator and prey species can directly alter the amount of resource available by interacting with it. Bifurcation and numerical analyses are presented to illustrate the system’s dynamical behavior. Taking the enrichment parameter of the resource as the bifurcation parameter, a Hopf bifurcation is found for some parameter ranges, which generate solutions that posses limit cycle behavior.     

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.     

Simultaneous boosting of source and sink capacities doubles tuber starch yield of potato plants

An important goal in biotechnological research is to improve the yield of crop plants. Here, we genetically modified simultaneously source and sink capacities in potato (Solanum tuberosum cv. Desirée) plants to improve starch yield. Source capacity was increased by mesophyll‐specific overexpression of a pyrophosphatase or, alternatively, by antisense expression of the ADP‐glucose pyrophosphorylase in leaves. Both approaches make use of re‐routing photoassimilates to sink organs at the expense of leaf starch accumulation. Simultaneous increase in sink capacity was accomplished by overexpression of two plastidic metabolite translocators, that is, a glucose 6‐phosphate/phosphate translocator and an adenylate translocator in tubers. Employing such a ‘pull’ approach, we have previously shown that potato starch content and yield can be increased when sink strength is elevated. In the current biotechnological approach, we successfully enhanced source and sink capacities by a combination of ‘pull’ and ‘push’ approaches using two different attempts. A doubling in tuber starch yield was achieved. This successful approach might be transferable to other crop plants in the future.     

An Approach to Integrating Environmental Considerations Within Managerial Decision‐Making

Recent environmental trends, including (1) an expansion of existing command and control directives, (2) the introduction of market‐based policy instruments, and (3) the adoption of extended producer responsibility, have created a need for new tools to help managerial decision‐making. To address this need, we develop a nonlinear mathematical programming model from a profit‐maximizing firm's perspective, which can be tailored as a decision‐support tool for firms facing environmental goals and constraints. We typify our approach using the specific context of diesel engine manufacturing and remanufacturing. Our model constructs are based on detailed interviews with top managers from two leading competitors in the medium and heavy‐duty diesel engine industry. The approach allows the incorporation of traditional operations‐planning considerations—in particular, capacity, production, and inventory—together with environmental considerations that range from product design through production to product end of life. A current hurdle to implementing such a model is the availability of input data. We therefore highlight the need not only to involve all departments within businesses but also for industrial ecologists and business managers to work together to implement meaningful decision models that are based on accurate and timely data and can have positive economic and environmental impact.     

High-throughput process development: determination of dynamic binding capacity using microtiter filter plates filled with chromatography resin

Steadily increasing demand for more efficient and more affordable biomolecule-based therapies put a significant burden on biopharma companies to reduce the cost of R&D activities associated with introduction of a new drug to the market. Reducing the time required to develop a purification process would be one option to address the high cost issue. The reduction in time can be accomplished if more efficient methods/tools are available for process development work, including high-throughput techniques. This paper addresses the transitions from traditional column-based process development to a modern high-throughput approach utilizing microtiter filter plates filled with a well-defined volume of chromatography resin. The approach is based on implementing the well-known batch uptake principle into microtiter plate geometry. Two variants of the proposed approach, allowing for either qualitative or quantitative estimation of dynamic binding capacity as a function of residence time, are described. Examples of quantitative estimation of dynamic binding capacities of human polyclonal IgG on MabSelect SuRe and of qualitative estimation of dynamic binding capacity of amyloglucosidase on a prototype of Capto DEAE weak ion exchanger are given. The proposed high-throughput method for determination of dynamic binding capacity significantly reduces time and sample consumption as compared to a traditional method utilizing packed chromatography columns without sacrificing the accuracy of data obtained.     

Profiling services for resource optimization and capacity planning in distributed systems

The capacity needs of online services are mainly determined by the volume of user loads. For large-scale distributed systems running such services, it is quite difficult to match the capacities of various system components. In this paper, a novel and systematic approach is proposed to profile services for resource optimization and capacity planning. We collect resource consumption related measurements from various components across distributed systems and further search for constant relationships between these measurements. If such relationships always hold under various workloads along time, we consider them as invariants of the underlying system. After extracting many invariants from the system, given any volume of user loads, we can follow these invariant relationships sequentially to estimate the capacity needs of individual components. By comparing the current resource configurations against the estimated capacity needs, we can discover the weakest points that may deteriorate system performance. Operators can consult such analytical results to optimize resource assignments and remove potential performance bottlenecks. In this paper, we propose several algorithms to support capacity analysis and guide operator’s capacity planning tasks. Our algorithms are evaluated with real systems and experimental results are also included to demonstrate the effectiveness of our approach.

A general analysis of resource allocation by competing individuals.

A linear model for population dynamics in a stationary stochastic environment is introduced based on linearizing the N-species Lotka-Volterra competition equations in discrete time. Iteration of the linear model shows the sequence of population sizes to be formed from a simple linear operation on the sequence of carrying capacities. The transfer function for this operation is calculated and the spectral properties of time series data on population size follow directly.The above approach is illustrated with a symmetrical two-species competition system assuming white noise variation in the carrying capacities. The results are interpreted in detail with the following ideas. (1) The intrinsic rate of increase governs the “responsiveness” of the population to changes in the carrying capacity; (2) one effect of competition is to reduce the “effective rate of increase” of the population. Increasing competition can produce effects identical to that of lowering the intrinsic rate of increase; (3) the other effect of competition is to communicate the stochastic variation in one species' carrying capacity to its competitors. The end result of this communication depends critically on the cross-correlation scheme among the carrying capacities of the competing species.     

Reaction networks and evolutionary game theory

The powerful mathematical tools developed for the study of large scale reaction networks have given rise to applications of this framework beyond the scope of biochemistry. Recently, reaction networks have been suggested as an alternative way to model social phenomena. In this “socio-chemical metaphor” molecular species play the role of agents’ decisions and their outcomes, and chemical reactions play the role of interactions among these decisions. From here, it is possible to study the dynamical properties of social systems using standard tools of biochemical modelling. In this work we show how to use reaction networks to model systems that are usually studied via evolutionary game theory. We first illustrate our framework by modeling the repeated prisoners’ dilemma. The model is built from the payoff matrix together with assumptions of the agents’ memory and recognizability capacities. The model provides consistent results concerning the performance of the agents, and allows for the examination of the steady states of the system in a simple manner. We further develop a model considering the interaction among Tit for Tat and Defector agents. We produce analytical results concerning the performance of the strategies in different situations of agents’ memory and recognizability. This approach unites two important theories and may produce new insights in classical problems such as the evolution of cooperation in large scale systems.     

Reducing mortality from anthrax bioterrorism: strategies for stockpiling and dispensing medical and pharmaceutical supplies

A critical question in planning a response to bioterrorism is how antibiotics and medical supplies should be stockpiled and dispensed. The objective of this work was to evaluate the costs and benefits of alternative strategies for maintaining and dispensing local and regional inventories of antibiotics and medical supplies for responses to anthrax bioterrorism. We modeled the regional and local supply chain for antibiotics and medical supplies as well as local dispensing capacity. We found that mortality was highly dependent on the local dispensing capacity, the number of individuals requiring prophylaxis, adherence to prophylactic antibiotics, and delays in attack detection. For an attack exposing 250,000 people and requiring the prophylaxis of 5 million people, expected mortality fell from 243,000 to 145,000 as the dispensing capacity increased from 14,000 to 420,000 individuals per day. At low dispensing capacities (<14,000 individuals per day), nearly all exposed individuals died, regardless of the rate of adherence to prophylaxis, delays in attack detection, or availability of local inventories. No benefit was achieved by doubling local inventories at low dispensing capacities; however, at higher dispensing capacities, the cost-effectiveness of doubling local inventories fell from 100,000 US dollars to 20,000 US dollars/life year gained as the annual probability of an attack increased from 0.0002 to 0.001. We conclude that because of the reportedly rapid availability of regional inventories, the critical determinant of mortality following anthrax bioterrorism is local dispensing capacity. Bioterrorism preparedness efforts directed at improving local dispensing capacity are required before benefits can be reaped from enhancing local inventories.     

Capacity Choice in a Large Market

We analyze endogenous capacity formation in a large frictional market with perfectly divisible goods. Each seller posts a price and decides on a capacity. The buyers base their decision on which seller to visit on both characteristics. In this setting we determine the conditions for the existence and uniqueness of a symmetric equilibrium. When capacity is unobservable there exists a continuum of equilibria. We show that the “best” of these equilibria leads to the same seller capacities and the same number of trades as the symmetric equilibrium under observable capacity.     

Small population instability and island settlement patterns

A model of extinction probability, based on the general theory of island biogeography [MacArthur and Wilson, 1967], is proposed for humans on oceanic islands; extinction probability is determined by island carrying capacity, frequency and amplitude of fluctuations in resources determining carrying capacity, and the net costs of contact and exchange between population units. The model predicts that extinction probability will determine island settlement patterns within an island group resulting in nonsettlement of islands with low carrying capacities and settlement of all islands with high carrying capacities. Data examined from the Marshall Islands tend to support the model. The model is extended to initial atoll colonization patterns. Possible requirements for initial settlement are suggested.Deceased.     

Optical method for the determination of the oxygen-transfer capacity of small bioreactors based on sulfite oxidation.

The growth of microorganisms may be limited by operating conditions which provide an inadequate supply of oxygen. To determine the oxygen-transfer capacities of small-scale bioreactors such as shaking flasks, test tubes, and microtiter plates, a noninvasive easy-to-use optical method based on sulfite oxidation has been developed. The model system of sodium sulfite was first optimized in shaking-flask experiments for this special application. The reaction conditions (pH, buffer, and catalyst concentration) were adjusted to obtain a constant oxygen transfer rate for the whole period of the sulfite oxidation reaction. The sharp decrease of the pH at the end of the oxidation, which is typical for this reaction, is visualized by adding a pH dye and used to measure the length of the reaction period. The oxygen-transfer capacity can then be calculated by the oxygen consumed during the complete stoichiometric transformation of sodium sulfite and the visually determined reaction time. The suitability of this optical measuring method for the determination of oxygen-transfer capacities in small-scale bioreactors was confirmed with an independent physical method applying an oxygen electrode. The correlation factor for the maximum oxygen-transfer capacity between the chemical model system and a culture of Pseudomonas putida CA-3 was determined in shaking flasks. The newly developed optical measuring method was finally used for the determination of oxygen-transfer capacities of different types of transparent small-scale bioreactors.     

Medium term planning of biopharmaceutical manufacture using mathematical programming

Regulatory pressures and capacity constraints are forcing the biopharmaceutical industry to consider employing multiproduct manufacturing facilities running on a campaign basis. The need for such flexible and cost-effective manufacture poses a significant challenge for planning and scheduling. This paper reviews the problem of planning and scheduling of biopharmaceutical manufacture and presents a methodology for the planning of multiproduct biopharmaceutical manufacturing facilities. The problem is formulated as a mixed integer linear program (MILP) to represent the relevant decisions required within the planning process and is tested on two typical biopharmaceutical industry planning problems. The proposed formulation is compared with an industrial rule based approach, which it outperforms in terms of profitability. The results indicate that the developed formulation offers an effective representation of the planning problem and would be a useful decision tool for manufacturers in the biopharmaceutical industry particularly at times of limited manufacturing capacity.     

Flexibility in manufacturing: A survey

This article is an attempt to survey the vast literature on flexibility in manufacturing that has accumulated over the last 10 to 20 years. The survey begins with a brief review of the classical literature on flexibility in economics and organization theory, which provides a background for manufacturing flexibility. Several kinds of flexibilities in manufacturing are then defined carefully along with their purposes, the means to obtain them, and some suggested measurements and valuations. Then we examine the interrelationships among the several flexibilities. Various empirical studies and analytical/optimization models dealing with these flexibilities are reported and discussed. The article concludes with suggestions for some possible future research directions.     

Spatially structured metapopulation models: global and local assessment of metapopulation capacity

We model metapopulation dynamics in finite networks of discrete habitat patches with given areas and spatial locations. We define and analyze two simple and ecologically intuitive measures of the capacity of the habitat patch network to support a viable metapopulation. Metapopulation persistence capacity lambda(M) defines the threshold condition for long-term metapopulation persistence as lambda(M)>delta, where delta is defined by the extinction and colonization rate parameters of the focal species. Metapopulation invasion capacity lambda(I) sets the condition for successful invasion of an empty network from one small local population as lambda(I)>delta. The metapopulation capacities lambda(M) and lambda(I) are defined as the leading eigenvalue or a comparable quantity of an appropriate "landscape" matrix. Based on these definitions, we present a classification of a very general class of deterministic, continuous-time and discrete-time metapopulation models. Two specific models are analyzed in greater detail: a spatially realistic version of the continuous-time Levins model and the discrete-time incidence function model with propagule size-dependent colonization rate and a rescue effect. In both models we assume that the extinction rate increases with decreasing patch area and that the colonization rate increases with patch connectivity. In the spatially realistic Levins model, the two types of metapopulation capacities coincide, whereas the incidence function model possesses a strong Allee effect characterized by lambda(I)=0. For these two models, we show that the metapopulation capacities can be considered as simple sums of contributions from individual habitat patches, given by the elements of the leading eigenvector or comparable quantities. We may therefore assess the significance of particular habitat patches, including new patches that might be added to the network, for the metapopulation capacities of the network as a whole. We derive useful approximations for both the threshold conditions and the equilibrium states in the two models. The metapopulation capacities and the measures of the dynamic significance of particular patches can be calculated for real patch networks for applications in metapopulation ecology, landscape ecology, and conservation biology.     

Chimpanzees fail to plan in an exchange task but succeed in a tool-using procedure

Planning has long been considered a uniquely human capacity. Lately, however, it has been shown that apes and a corvid species act now to derive a material future benefit. Since primates are highly social animals and their sociality is considered a strong selective force that resulted in complex cognitive capacities, planning is also expected in social situations. Unfortunately, prompting from social partners cannot be excluded in a social setting. Therefore, we controlled for this factor by testing the capacity to plan in chimpanzees using an exchange paradigm, that involves both a material and a social component, and a tool-use paradigm, similar to the one used on two other ape species. All chimpanzees failed to plan in the exchange task, but three individuals showed planning behavior in the tool-use task. Our methods controlled for the fact that chimpanzees were not prompted by the visibility of the reward at the moment of planning and also could not repeat a previously acquired routine. The best interpretation for our results is that chimpanzees can plan. However, planning was limited to the situation where the action to attain the future benefit only depended on a chimpanzee's own behavior.     

A branch and cut algorithm for the container shipping network design problem

The network design problem in liner shipping is of increasing importance in a strongly competitive market where potential cost reductions can influence market share and profits significantly. In this paper the network design and fleet assignment problems are combined into a mixed integer linear programming model minimizing the overall cost. To better reflect the real-life situation we take into account the cost of transhipment, a heterogeneous fleet, route dependent capacities, and butterfly routes. To the best of our knowledge it is the first time an exact solution method to the problem considers transhipment cost. The problem is solved with branch-and-cut using clover and transhipment inequalities. Computational results are reported for instances with up to 15 ports.     

Cultural transmission and biological markets

Active cultural transmission of fitness-enhancing behavior (sometimes called “teaching”) can be seen as a costly strategy: one for which its evolutionary stability poses a Darwinian puzzle. In this article, we offer a biological market model of cultural transmission that substitutes or complements existing kin selection-based proposals for the evolution of cultural capacities. We demonstrate how a biological market can account for the evolution of teaching when individual learners are the exclusive focus of social learning (such as in a fast-changing environment). We also show how this biological market can affect the dynamics of cumulative culture. The model works best when it is difficult to have access to the observation of the behavior without the help of the actor. However, in contrast to previous non-mathematical hypotheses for the evolution of teaching, we show how teaching evolves, even when innovations are insufficiently opaque and therefore vulnerable to acquisition by emulators via inadvertent transmission. Furthermore, teaching in a biological market is an important precondition for enhancing individual learning abilities.     

Interspecific dietary diversity has little influence on pathways of glucose metabolism in liver and heart of piranhas and pacus (family Serrasalmidae)

The Serrasalmidae is a speciose family of Neotropical freshwater fishes with diverse interspecies dietary preferences, from the herbivorous or frugivorous pacus to the omnivorous or carnivorous piranhas. The Serrasalmidae is an ideal comparative model to explore the biochemical correlates of dietary preference. For example, debate exists about whether variation in dietary preference among fishes influences the capacities for de novo glucose synthesis (gluconeogenesis) or glucose use as metabolic fuel (glycolysis). We predicted that carnivory in piranhas would be associated with an enhanced gluconeogenic capacity compared with the herbivorous pacus, because carnivores consume less carbohydrate. As a corollary, we expected similar glycolytic capacities at a major site of glucose use (heart) in fishes with different diets. We measured activities of key enzymes of gluconeogenesis and the opposing reactions of glycolysis in liver (the primary gluconeogenic site) and heart of five serrasalmid species showing an interspecies dietary gradient from herbivory to omnivory to carnivory. The interspecific variation in enzyme activities was, in general, unrelated to dietary preference. Glycolytic capacity in heart was lower in herbivores but this may be related to non-diet factors. Among serrasalmid fishes, the enzymatic capacities of glucose metabolism are not overtly influenced by interspecific divergence of dietary preference.