Real-time software methodologies: Are they suitable for developing Manufacturing control software?

Computer-Integrated Manufacturing (CIM) systems may be classified as real-time systems. Hence, the applicability of methodologies that are developed for specifying, designing, implementing, testing, and evolving real-time software is investigated in this article. The paper highlights the activities of the software development process. Among these activities, a great emphasis is placed on automating the software requirements specification activity, and a set of formal models and languages for specifying these requirements is presented. Moreover, a synopsis of the real-time software methodologies that have been implemented by the academic and industrial communities is presented together with a critique of the strengths and weaknesses of these methodologies. The possible use of the real-time methodologies in developing the control software of efficient and dependable manufacturing systems is explored. In these systems, efficiency is achieved by increasing the level of concurrency of the operations of a plan, and by scheduling the execution of these operations with the intent of maximizing the utilization of the devices of their systems. On the other hand, dependability requires monitoring the operations of these systems. This monitoring activity facilitates the detection of faults that may occur when executing the scheduled operations of a plan, recovering from these faults, and, whenever feasible, resuming the original schedule of the system. The paper concludes that the set of surveyed methodologies may be used to develop the real-time control software of efficient and dependable manufacturing systems. However, an integrated approach to planning, scheduling, and monitoring the operations of these systems will significantly enhance their utility, and no such approach is supported by any of these methodologies.     

A pattern-directed approach to flexible manufacturing: A framework for intelligent scheduling,learning, and control

The planning, scheduling, and control of manufacturing systems can all be viewed as problem-solving activities. In flexible manufacturing systems (FMSs), the computer program carrying out these problem-solving activities must additionally be able to handle the shorter lead time, the flexibility of job routing, the multiprocessing environment, the dynamic changing states, and the versatility of machines. This article presents an artificial intelligence (AI) method to perform manufacturing problem solving. Since the method is driven by manufacturing scenarios represented by symbolic patterns, it is referred to as pattern-directed. The method is based on three AI techniques. The first is the pattern-directed inference technique to capture the dynamic nature of FMSs. The second is the nonlinear planning technique to construct schedules and assign resources. The third is the inductive learning method to generate the pattern-directed heuristics. This article focuses on solving the FMS scheduling problem. In addition, this article reports the computation results to evaluate the utility of various heuristic functions, to identify important design parameters, and to analyze the resulting computational performance in using the pattern-directed approach for manufacturing problem-solving tasks such as scheduling.     

Balancing flexibility for the employer and the employee: a case study of the development of annualized hours employment contracts

As with many forms of flexible working, Annualized Hours (AH) systems offer potential benefits to both the employer and the employee. However, the flexibility requirements of employers and employees often conflict. Therefore, when a large food manufacturing organization decided to redesign its AH system, it employed an independent consultancy to act as neutral third party. The consultancy provided technical expertise and assistance in developing an AH system that optimised productivity and was acceptable to the workforce. Data are presented, obtained from focus groups conducted throughout the organization, describing some of the potential difficulties of implementing an AH system. Drawing upon these data, a number of new AH systems were proposed and modelled using specialist software tools. The design process is described, together with the advantages and difficulties associated with use of the software tools. It is concluded that the key elements in the process of designing AH systems are centred around issues of trust and communication; the involvement of a broad range of interested parties, through a process of carefully managed group facilitation; and the need for adequate technical support in the development and evaluation of AH systems.     

Production activity control: A practical approach to scheduling

There is a widely perceived gap within the domain of scheduling for manufacturing systems, namely, many of the methods employed by production supervisors are quite different from those developed by researchers. In a sense, this inconsistency highlights the important fact that much scheduling research has failed to win approval where it matters most, namely, within the manufacturing system. In this article, we argue for a practical approach to scheduling for manufacturing systems, one that we believe can narrow, and possibly bridge, the gap between theory and practice. This approach is based upon a well-defined and modular architecture for scheduling, termedproduction activity control. This architecture is the foundation of our proposed solution to scheduling, since it provides a coherent blueprint for the synthesis of information technology and scheduling strategies. The result of this synthesis is a design tool for production activity control, which allows for detailed and disciplined experimentation with a range of scheduling strategies in a controlled and simulated environment. Due to the unique modular property of the design tool, these strategies may then be implemented live in a flexible manufacturing facility, hence narrowing the gap between scheduling theory and manufacturing practice. Our overall approach is tested through an appropriate implementation in a modern electronics assembly plant.     

The Application and Evaluation of Banker's Algorithm for Deadlock-Free Buffer Space Allocation in Flexible Manufacturing Systems

Deadlock-free operation is essential for operating highly automated manufacturing systems. The seminal deadlock avoidance procedure, Banker's algorithm, was developed for computer operating systems, an environment where very little information regarding the future resource requirements of executing processes is known. Manufacturing researchers have tended to dismiss Banker's algorithm as too conservative in the manufacturing environment where future resource requirements are well defined by part routes. In this work, we investigate this issue by developing variants of Banker's algorithm applicable to buffer space allocation in flexible manufacturing. We show that these algorithms are not overly conservative and that, indeed, Banker's approach can provide very good operational flexibility when properly applied to the manufacturing environment.     

The influence of planning unit characteristics on the efficiency and spatial pattern of systematic conservation planning assessments

Systematic conservation planning is a widely used approach for designing protected area systems and ecological networks. This generally involves dividing the planning region into a series of planning units and using computer software to select portfolios of these units that meet specified conservation targets whilst minimising conservation costs. Previous research has shown that changing the size and shape of these planning units can alter the apparent spatial characteristics of the underlying data and thus influence conservation assessment results. However, this may be less problematic when using newer software that can account for additional constraints based on portfolio costs and fragmentation levels. Here we investigate these issues using a dataset from southern Africa and measure the extent to which changing planning unit shape, size and baseline affects the results of conservation planning assessments. We show that using hexagonal planning units instead of squares produces more efficient and less fragmented portfolios and that using larger planning units produces portfolios that are less efficient but more likely to identify the same priority areas. We also show that using real-world constraints in the analysis, based on reducing socio-economic costs and minimising fragmentation levels, reduces the influence of planning unit characteristics on the results and so argue that future studies should adopt a similar approach when investigating factors that influence conservation assessments.     

Predictable quality of service atop degradable distributed systems

High performance and distributed computing systems such as peta-scale, grid and cloud infrastructure are increasingly used for running scientific models and business services. These systems experience large availability variations through hardware and software failures. Resource providers need to account for these variations while providing the required QoS at appropriate costs in dynamic resource and application environments. Although the performance and reliability of these systems have been studied separately, there has been little analysis of the lost Quality of Service (QoS) experienced with varying availability levels. In this paper, we present a resource performability model to estimate lost performance and corresponding cost considerations with varying availability levels. We use the resulting model in a multi-phase planning approach for scheduling a set of deadline-sensitive meteorological workflows atop grid and cloud resources to trade-off performance, reliability and cost. We use simulation results driven by failure data collected over the lifetime of high performance systems to demonstrate how the proposed scheme better accounts for resource availability.     

DNA Assembly in 3D Printed Fluidics

The process of connecting genetic parts—DNA assembly—is a foundational technology for synthetic biology. Microfluidics present an attractive solution for minimizing use of costly reagents, enabling multiplexed reactions, and automating protocols by integrating multiple protocol steps. However, microfluidics fabrication and operation can be expensive and requires expertise, limiting access to the technology. With advances in commodity digital fabrication tools, it is now possible to directly print fluidic devices and supporting hardware. 3D printed micro- and millifluidic devices are inexpensive, easy to make and quick to produce. We demonstrate Golden Gate DNA assembly in 3D-printed fluidics with reaction volumes as small as 490 nL, channel widths as fine as 220 microns, and per unit part costs ranging from $0.61 to $5.71. A 3D-printed syringe pump with an accompanying programmable software interface was designed and fabricated to operate the devices. Quick turnaround and inexpensive materials allowed for rapid exploration of device parameters, demonstrating a manufacturing paradigm for designing and fabricating hardware for synthetic biology.     

Plato: a genetic algorithm approach to run-time reconfiguration in?autonomic computing systems

Increasingly, applications need to be able to self-reconfigure in response to changing requirements and environmental conditions. Autonomic computing has been proposed as a means for automating software maintenance tasks. As the complexity of adaptive and autonomic systems grows, designing and managing the set of reconfiguration rules becomes increasingly challenging and may produce inconsistencies. This paper proposes an approach to leverage genetic algorithms in the decision-making process of an autonomic system. This approach enables a system to dynamically evolve target reconfigurations at run time that balance tradeoffs between functional and non-functional requirements in response to changing requirements and environmental conditions. A key feature of this approach is incorporating system and environmental monitoring information into the genetic algorithm such that specific changes in the environment automatically drive the evolutionary process towards new viable solutions. We have applied this genetic-algorithm based approach to the dynamic reconfiguration of a collection of remote data mirrors, demonstrating an effective decision-making method for diffusing data and minimizing operational costs while maximizing data reliability and network performance, even in the presence of link failures.     

A distributed knowledge-based approach to flexible automation: The contract net framework

This article applied distributed artificial intelligence to the real-time planning and control of flexible manufacturing systems (FMS) consisting of asynchronous manufacturing cells. A knowledge-based approach is used to determine the course of action, resource sharing, and processor assignments. Within each cell there is an embedded automatic planning system that executes dynamic scheduling and supervises manufacturing operations. Because of the decentralized control, real-time task assignments are carried out by a negotiation process among cell hosts. The negotiation process is modeled by augmented Petri nets —the combination of production rules and Petri nets—and is excuted by a distributed, rule-based algorithm.     

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.     

An efficient heuristic for scheduling batches of parts in a flexible flow system

Flexible manufacturing systems (FMSs) are a class of automated systems that can be used to improve productivity in batch manufacturing. Four stages of decision making have been defined for an FMS—the design, planning, scheduling, and control stages. This research focuses on the planning stage, and specifically in the area of scheduling batches of parts through the system. The literature to date on the FMS planning stage has mostly focused on the machine grouping, tool loading, and parttype selection problems. Our research carries the literature a step further by addressing the problem of scheduling batches of parts. Due to the use of serial-access material-handling systems in many FMSs, the batch-scheduling problem is modeled for a flexible flow system (FFS). This model explicitly accounts for setup times between batches that are dependent on their processing sequence. A heuristic procedure is developed for this batch-scheduling problem—the Maximum Savings (MS) heuristic. The MS heuristic is based upon the savings in time associated with a particular sequence and selecting the one with the maximum savings. It uses a two-phase method, with the savings being calculated in phase I, while a branch-and-bound procedure is employed to seek the best heuristic solution in phase II. Extensive computational results are provided for a wide variety of problems. The results show that the MS heuristic provides good-quality solutions.     

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.     

Towards a global terrestrial species monitoring program

The Convention on Biological Diversity's strategic plan lays out five goals: “(A) address the underlying causes of biodiversity loss by mainstreaming biodiversity across government and society; (B) reduce the direct pressures on biodiversity and promote sustainable use; (C) improve the status of biodiversity by safeguarding ecosystems, species and genetic diversity; (D) enhance the benefits to all from biodiversity and ecosystem services; (E) enhance implementation through participatory planning, knowledge management and capacity building.” To meet and inform on the progress towards these goals, a globally coordinated approach is needed for biodiversity monitoring that is linked to environmental data and covers all biogeographic regions. During a series of workshops and expert discussions, we identified nine requirements that we believe are necessary for developing and implementing such a global terrestrial species monitoring program. The program needs to design and implement an integrated information chain from monitoring to policy reporting, to create and implement minimal data standards and common monitoring protocols to be able to inform Essential Biodiversity Variables (EBVs), and to develop and optimize semantics and ontologies for data interoperability and modelling. In order to achieve this, the program needs to coordinate diverse but complementary local nodes and partnerships. In addition, capacities need to be built for technical tasks, and new monitoring technologies need to be integrated. Finally, a global monitoring program needs to facilitate and secure funding for the collection of long-term data and to detect and fill gaps in under-observed regions and taxa. The accomplishment of these nine requirements is essential in order to ensure data is comprehensive, to develop robust models, and to monitor biodiversity trends over large scales. A global terrestrial species monitoring program will enable researchers and policymakers to better understand the status and trends of biodiversity.     

On the Consequences of Information Delays in the Scheduling of Semi-Automated Flexible Machines

Manufacturing systems with varying levels and types of flexibility employ alternative scheduling strategies to exploit flexibility for performance enhancement. Scheduling decisions in manufacturing systems are influenced by time delays due to information handling activities such as information collection, transfer, and processing. More specifically, scheduling strategies implicitly involve information intensive activities that may entail significant time delays for implementation, depending on the extant shop floor automation and integration within a flexible system. These are information delays and we believe that most contemporary flexible systems must inherently cope with some level of information delay when implementing on-line scheduling strategies. This paper conceptualizes the manifestation of information delays in the context of scheduling decisions within flexible systems through the definition of three key delay modes: (i) Mode 1 information-transfer delay; (ii) Mode 2 decision-implementation delay; and (iii) Mode 3 status-review delay. We then stress the need and importance of devising suitable on-line scheduling strategies for countering the effect of information delays by demonstrating the efficacy of a novel scheduling strategy on a single machine. While opening a new scheduling dimension with potential research ramifications, this paper highlights the fact that the concept of information delay can effectively capture the synergism issues related with flexibility, integration, and automation in the context of scheduling decisions within semi-automated flexible systems.     

A reference business process for ecological niche modelling

Ecological niche modelling combines species occurrence points with environmental raster layers in order to obtain models for describing the probabilistic distribution of species. The process to generate an ecological niche model is complex. It requires dealing with a large amount of data, use of different software packages for data conversion, for model generation and for different types of processing and analyses, among other functionalities. A software platform that integrates all requirements under a single and seamless interface would be very helpful for users. Furthermore, since biodiversity modelling is constantly evolving, new requirements are constantly being added in terms of functions, algorithms and data formats. This evolution must be accompanied by any software intended to be used in this area. In this scenario, a Service-Oriented Architecture (SOA) is an appropriate choice for designing such systems. According to SOA best practices and methodologies, the design of a reference business process must be performed prior to the architecture definition. The purpose is to understand the complexities of the process (business process in this context refers to the ecological niche modelling problem) and to design an architecture able to offer a comprehensive solution, called a reference architecture, that can be further detailed when implementing specific systems. This paper presents a reference business process for ecological niche modelling, as part of a major work focused on the definition of a reference architecture based on SOA concepts that will be used to evolve the openModeller software package for species modelling. The basic steps that are performed while developing a model are described, highlighting important aspects, based on the knowledge of modelling experts. In order to illustrate the steps defined for the process, an experiment was developed, modelling the distribution of Ouratea spectabilis (Mart.) Engl. (Ochnaceae) using openModeller. As a consequence of the knowledge gained with this work, many desirable improvements on the modelling software packages have been identified and are presented. Also, a discussion on the potential for large-scale experimentation in ecological niche modelling is provided, highlighting opportunities for research. The results obtained are very important for those involved in the development of modelling tools and systems, for requirement analysis and to provide insight on new features and trends for this category of systems. They can also be very helpful for beginners in modelling research, who can use the process and the experiment example as a guide to this complex activity.     

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.     

Multiple-Objective Scheduling for the Hierarchical Control of Flexible Manufacturing Systems

This paper presents a hierarchical approach to scheduling flexible manufacturing systems (FMSs) that pursues multiple performance objectives and considers the process flexibility of incorporating alternative process plans and resources for the required operations. The scheduling problem is solved at two levels: the shop level and the manufacturing system level. The shop level controller employs a combined priority index developed in this research to rank shop production orders in meeting multiple scheduling objectives. To overcome dimensional complexity and keep a low level of work-in-process inventory, the shop controller first selects up to three production orders with the highest ranking as candidates and generates all possible release sequences for them, with or without multitasking. These sequences are conveyed to the manufacturing system controller, who then performs detailed scheduling of the machines in the FMS using a fixed priority heuristic for routing parts of multiple types while considering alternative process plans and resources for the operations. The FMS controller provides feedback to the shop controller with a set of suggested detailed schedules and projected order completion times. On receiving these results, the shop controller further evaluates each candidate schedule using a multiple-objective function and selects the best schedule for execution. This allows multiple performance objectives of an FMS to be achieved by the integrated hierarchical scheduling approach.     

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.