The measurement of flexibility in manufacturing systems

This article provides a theoretical basis for measuring the flexibility of manufacturing systems. The concept of multiple levels of measures (necessary, capability, actual, inflexibility, and optimality) for each flexibility type is introduced. Capability and actual measures are then developed for machine, routing, process, product, and volume flexibilities. For each of these flexibility types, a state defining variable is identified. A measure of flexibility is then derived by computing either, (i) the change effort expended in moving between states, (ii) the drop in system performance in moving between states, (iii) a general or physical scale of difference between two successive states, or (iv) a measure combining all three. The use of the developed measures is illustrated via a two-facility example.     

Flexibility in manufacturing and services: achievements, insights and challenges

The concept of flexibility has attracted considerable interest in the last 25 years in the context of manufacturing. This paper develops a framework for thinking about flexibility in the context of making decisions about the design and operation of systems in either manufacturing or service environments. Three different aspects of flexibility are defined: prior flexibility, state flexibility and action flexibility, and the issues in the measurement of flexibility are discussed. The use of flexibility ideas by industry in manufacturing and services is reviewed and key contributions to the academic literature are summarized. Major issues and insights arising from a focus on flexibility are discussed. The paper concludes with some challenges for future research.     

Conformational flexibility and its functional significance in some protein molecules

Crystallography has contributed much to our knowledge of protein flexibility and here are described some examples of large-scale segmental flexibilities discovered by X=ray diffraction. These examples indicate that flexibility may be required for enzymatic catalysis and other functions of proteins, and also for their regulation.     

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.     

A modeling approach for evaluating capacity flexibilities in uncertain markets

The flexibility of production capacities is a means for coping with the challenges in today’s market environment, especially when dealing with strong fluctuations in customers’ demands. The reliable planning and evaluation of these capacities and their inherent flexibilities are considered an important task for many companies. This paper presents a capacity/cost model that considers the impact of market uncertainties and the corresponding capacity flexibilities. It proposes a demand forecasting method, a modeling approach for capacity-related flexibilities and the analysis of the economical correlation between available and required capacities. Based on this, capacity planning can be optimized using this model. The different steps of applying this modeling approach are illustrated with the aid of an example.     

Effectiveness of flexible routing control

Flexibility in part process representation and in highly adaptive routing algorithms are two major sources for improvement in the control of flexible manufacturing systems (FMSs). This article reports the investigation of the impact of these two kinds of flexibilities on the performance of the system. We argue that, when feasible, the choices of operations and sequencing of the part process plans should be deferred until detailed knowledge about the real-time factory state is available. To test our ideas, a flexible routing control simulation system (FRCS) was constructed and a programming language for modeling FMS part process plans, control strategies, and environments of the FMS was designed and implemented. In addition, a scheme for implementing flexible process routing called data flow dispatching rule (DFDR) was derived. The simulation results indicate that flexible processing can reduce mean flow time while increasing system throughput and machine utilization. We observed that this form of flexibility makes automatic load balancing of the machines possible. On the other hand, it also makes the control and scheduling process more complicated and calls for new control algorithms.     

Business Process Reengineering and Flexibility: A Case for Unification

Business process reengineering (BPR) offers a radical approach to improving the performance of an organization. However, although there have been successes BPR is recognized as a high-risk activity, prone to failure. There are a variety of reasons for this and this paper highlights one which is argued to be the lack of attention that BPR pays to flexibility and its inability to cope with a changing environment. The purpose of this article is to raise the issue of flexibility within BPR and an approach is taken that examines flexibility in other business functional areas, such as manufacturing, architecture, information systems, and organizational strategy, where there is an extensive literature that indicates the importance of flexibility. The lessons from these other areas are identified and some of the implications for BPR are highlighted. A number of proposals are made including the suggestion that a form of “flexibility analysis” be adopted as a stage in BPR projects. It is argued that this would help to move the focus of a BPR project away from the current requirements toward a longer term, more flexible, enduring set of requirements. Flexibility analysis also ensures analysis of the kinds of changes that might be required over time, and how such change could be accommodated in the reengineered processes.     

Definition and Classification of Manufacturing Flexibility Types and Measures

Flexibility is one of the most sought-after properties in modern manufacturing systems. Despite this interest, flexibility remains poorly understood in theory and poorly utilized in practice. One reason for this is the lack of general agreement on how to define flexibility: over 70 terms (types and measures) can be found in the literature. This paper concerns developing a framework and classification scheme for use in defining and classifying the various terms regarding flexibility found in manufacturing. The framework consists of six attributes: level of manufacturing requirements specification, manufacturing system specification, manufacturing environment specification, flexibility dimension, flexibility measurement approach, and time frame. A six-field hybrid classification scheme is developed based on this framework. The framework serves as a guide for developing new flexibility terms, whereas the classification scheme provides a mechanism for summarizing the important aspects of and assumptions behind a given term. The approach is demonstrated by using the classification scheme to classify over 50 existing flexibility terms. The results indicate that the classification scheme is an effective tool to aid in understanding different flexibility terms and how they compare to one another. At the same time, the difficulty of the classification exercise indicates the need for a suitable framework when defining such terms.     

Interconversion of functional motions between mesophilic and thermophilic adenylate kinases

Dynamic properties are functionally important in many proteins, including the enzyme adenylate kinase (AK), for which the open/closed transition limits the rate of catalytic turnover. Here, we compare our previously published coarse-grained (double-well Gō) simulation of mesophilic AK from E. coli (AKmeso) to simulations of thermophilic AK from Aquifex aeolicus (AKthermo). In AKthermo, as with AKmeso, the LID domain prefers to close before the NMP domain in the presence of ligand, but LID rigid-body flexibility in the open (O) ensemble decreases significantly. Backbone foldedness in O and/or transition state (TS) ensembles increases significantly relative to AKmeso in some interdomain backbone hinges and within LID. In contact space, the TS of AKthermo has fewer contacts at the CORE-LID interface but a stronger contact network surrounding the CORE-NMP interface than the TS of AKmeso. A "heated" simulation of AKthermo at 375K slightly increases LID rigid-body flexibility in accordance with the "corresponding states" hypothesis. Furthermore, while computational mutation of 7 prolines in AKthermo to their AKmeso counterparts produces similar small perturbations, mutation of these sites, especially positions 8 and 155, to glycine is required to achieve LID rigid-body flexibility and hinge flexibilities comparable to AKmeso. Mutating the 7 sites to proline in AKmeso reduces some hinges' flexibilities, especially hinge 2, but does not reduce LID rigid-body flexibility, suggesting that these two types of motion are decoupled in AKmeso. In conclusion, our results suggest that hinge flexibility and global functional motions alike are correlated with but not exclusively determined by the hinge residues. This mutational framework can inform the rational design of functionally important flexibility and allostery in other proteins toward engineering novel biochemical pathways.     

Towards an Integration of Process Planning and Production Planning and Control for Flexible Manufacturing Systems

This introduction article attempts to present some major issues relating to the integration of process planning and production planning and control (PPC) for flexible manufacturing systems (FMSs). It shows that the performance of an FMS can be significantly improved and FMS capabilities more effectively utilized by integrating process planning and PPC functions. The various types of flexibility to be planned and provided for in process planning and manufacturing are summarized in the article, as well as emerging conceptual frameworks for integration, along with their implementation requirements and problems. Distinctive elements that differentiate these frameworks, such as the extent of integration of process planning and PPC activities, number of alternative process plans, and the time at which numerical control programs are generated, are discussed, followed by a brief summary of the articles compiled for this special issue.     

Mechanical implications of the domain structure of fiber-forming collagens: comparison of the molecular and fibrillar flexibilities of the alpha1-chains found in types I-III collagen

Fibrillar collagens store, transmit and dissipate elastic energy during tensile deformation. Results of previous studies suggest that the collagen molecule is made up of alternating rigid and flexible domains, and extension of the flexible domains is associated with elastic energy storage. In this study, we model the flexibility of the alpha1-chains found in types I-III collagen molecules and microfibrils in order to understand the molecular basis of elastic energy storage in collagen fibers by analysing the areas under conformational plots for dipeptide sequences. Results of stereochemical modeling suggest that the collagen triple helix is made up of rigid and flexible domains that alternate with periods that are multiples of three amino acid residues. The relative flexibility of dipeptide sequences found in the flexible regions is about a factor of five higher than that found for the flexibility of the rigid regions, and the flexibility of types II and III collagen molecules appears to be higher than that found for the type I collagen molecule. The different collagen alpha1-chains were compared by correlating the flexibilities. The results suggest that the flexibilities of the alpha1-chains of types I and III collagen are more closely related than the flexibilities of the alpha1-chains in types I and II and II and III collagen. The flexible domains found in the alpha1-chains of types I-III collagen were found to be conserved in the microfibril and had periods of about 15 amino acid residues and multiples thereof. The flexibility profiles of types I and II collagen microfibrils were found to be more highly correlated than those for types I and III and II and III. These results suggest that the domain structure of the alpha1-chains found in types I-III collagen is an efficient means for storage of elastic energy during stretching while preserving the triple helical structure of the overall molecule. It is proposed that all collagens that form fibers are designed to act as storage elements for elastic energy. The function of fibers rich in type I collagen is to store and then transmit this energy while fibers rich in types II and III collagen may store and then reflect elastic energy for dissipation through viscous fibrillar slippage. Impaired elastic energy storage by extracellular matrices may lead to cellular damage and changes in signaling by mechanochemical transduction at the extracellular matrix-cell interface.     

DNA动力学柔性的统计力学模型

考虑碱基对之间的非紧邻相互作用、涨落的序列依赖效应和非对称涨落,提出了DNA构象的统计力学模型,给出了DNA柔性的新定义。作为模型的应用,对12种三核苷酸重复序列的动力学柔性作了预测。理论预测与其它方法得到的结论比较,有很好的一致性。对模型和结论的理论意义作了讨论。     

Reliability analysis of flexible manufacturing systems

High productivity is the primary goal of flexible manufacturing systems (FMSs) in which semi-independent workstations are integrated using automated material-transport systems and hierarchical local networks. Availability of various subsystems and of the system as a whole is a prerequisite for achieving functional integration as well as high throughput. An FMS also has inherent routing and operation flexibilities that provide it with a certain degree of fault tolerance. A certain volume of production can thus be maintained in the face of subsystem (i.e., machines, robots, material handling system, etc.) failures. In this article, we propose two reliability measures, namely, part reliability (PR) and FMS reliability (FMSR) for manufacturing systems and present algorithms to evaluate them. We also consider the dynamic or time-dependent reliability analysis as a natural generalization of the static analysis. The methods outlined use an algorithm that generates process-spanning graphs (PSGs), which are used to evaluate the reliability measures.     

LIMS in the manufacturing environment

The type of laboratory that implements a LIMS is very important in determining the requirements of the LIMS. This article focuses on the requirements for a manufacturing LIMS. The objectives of a manufacturing laboratory that a LIMS should support are presented. Issues that should be considered in the initial planning stage of implementing a manufacturing LIMS are discussed. Functional requirements for a manufacturing LIMS examined in the article are the ability to: (1) handle various material types, (2) grade products, (3) allow flexibility in test method configuration, (4) handle data limits and variable sets of data. (5) revise and track test methods and specifications, and (6) maintain a customer and/or supplier database.     

A Dynamic Tool Requirement Planning Model for Flexible Manufacturing Systems

Despite their strategic potential, tool management issues in flexible manufacturing systems (FMSs) have received little attention in the literature. Nonavailability of tools in FMSs cuts at the very root of the strategic goals for which such systems are designed. Specifically, the capability of FMSs to economically produce customized products (flexibility of scope) in varying batch sizes (flexibility of volume) and delivering them on an accelerated schedule (market response time) is seriously hampered when required tools are not available at the time needed. On the other hand, excess inventory of tools in such systems represents a significant cost due to the expensive nature of FMS tool inventory. This article constructs a dynamic tool requirement planning (DTRP) model for an FMS tool planning operation that allows dynamic determination of the optimal tool replenishments at the beginning of each arbitrary, managerially convenient, discrete time period. The analysis presented in the article consists of two distinct phases: In the first phase, tool demand distributions are obtained using information from manufacturing production plans (such as master production schedule (MPS) and material requirement plans (MRP)) and general tool life distributions fitted on actual time-to-failure data. Significant computational reductions are obtained if the tool failure data follow a Weibull or Gamma distribution. In the second phase, results from classical dynamic inventory models are modified to obtain optimal tool replenishment policies that permit compliance with such FMS-specific constraints as limited tool storage capacity and part/tool service levels. An implementation plan is included.     

A “goodness test” for operational measures of manufacturing flexibility

After more than a decade of research on measurement of manufacturing flexibility, it is now recognized that measures of flexibility are, by their very nature, user- and/or situation-specific. In such an environment, a set of principles that could be used by practitioners to test the goodness of metrics which they devise (to suit the requirements of their particular application) will be most useful. This article fulfills the above stated need by developing such a test. This test is then applied to some flexibility measures suggested in recent studies, and their strengths and/or weaknesses are pointed out.     

Flexible and reconfigurable manufacturing systems paradigms

Reconfigurable Manufacturing System (RMS) is a new manufacturing systems paradigm that aims at achieving cost-effective and rapid system changes, as needed and when needed, by incorporating principles of modularity, integrability, flexibility, scalability, convertibility, and diagnosability. RMS promises customized flexibility on demand in a short time, while Flexible Manufacturing Systems (FMSs) provides generalized flexibility designed for the anticipated variations and built-in a priori. The characteristics of the two paradigms are outlined and compared. The concept of manufacturing system life cycle is presented. The main types of flexibility in manufacturing systems are discussed and contrasted with the various reconfiguration aspects including hard (physical) and soft (logical) reconfiguration. The types of changeability and transformability of manufacturing systems, their components as well as factories, are presented along with their enablers and compared with flexibility and reconfigurability. The importance of having harmonized human-machine manufacturing systems is highlighted and the role of people in the various manufacturing paradigms and how this varies in pursuit of productivity are illustrated. Finally, the industrial and research challenges presented by these manufacturing paradigms are discussed.     

A Classification for Hoist Scheduling Problems

Electroplating lines are totally automated manufacturing systems that are used to cover parts with a coat of metal. They consist of a set of tanks between which the parts to be treated are transported by one or several hoists. Scheduling the movements of these hoists is commonly called a hoist scheduling problem (HSP) in the literature. But the assumptions and constraints that must be taken into account greatly depend on the production environment (physical system, manufacturing specifications, and management policies). Consequently, there exist several classes of HSPs. The systematic frameworks usually used to classify deterministic scheduling problems do not allow distinguishing between these various kinds of HSPs. Therefore, identifying the scope of each published work and comparing the various proposed scheduling methods turn out to be difficult. Thus, this article presents notation for scheduling problems in electroplating systems, to make the specification of problem types and the identification of studied problem instances easier. An associated typology gives a survey of the literature and demonstrates the usefulness of the proposed classification scheme.     

Dynamic flexibility in the Escherichia coli genome.

Empirical rules based on tetranucleotide parameters were presented to predict the structural parameters twist (Omega), roll (rho), tilt (tau) and slide (D(y)). A statistical mechanical model was used to analyze the flexibility of the Escherichia coli genome. The replication terminus region displayed a low level of flexibility. A strong correlation can be seen between G+C content and flexibility. Average flexibilities in the coding regions were found to be significantly larger than those in non-coding regions. The flexible characteristics in the 5'-neighborhood of the coding regions and in three class sigma promoter sequences in the E. coli genome were also analyzed.     

A molecular dynamics analysis of the GCC-box binding domain in ethylene-responsive element binding factors

Ethylene-responsive element (ERE) binding factors is responsible for a consensus nucleotide sequence AGCCGCC (GCC-box) binding in many important process of plant growing through gene regulation and mediating signal transduction pathways in response to environmental stress. The GCC-box binding domain (GBD) as a novel fold for DNA recognition has been analyzed by means of molecular dynamics. The simulations show that the complex of GBD-DNA trajectories show similar fluctuations in the atomic positions as uncomplexed, particularly at three beta strands involving DNA binding. The calculations of entropy also affirm that GBD flexibility is basically similar for two ligation states. Further, the two complexation states present similar patterns of concerted motions, indicating that the bound DNA cannot alter GBD flexibility. It is inferred that the flexibility of GBD molecule is independent of its ligation state. So in the protein-DNA recognition, the GBD cannot be easily induced while DNA shows better flexibility. Comparison between simulations of unligated GBD and the complexed GBD (in isolation or DNA-bound) reveals intrinsic flexibilities in some certain parts of the molecule play a key role in DNA recognition. In addition, MD simulation identifies that water molecule may mediate interaction between GBD and DNA.