A generic approach to measuring the machine flexibility of manufacturing systems

Despite extensive studies on the flexibility of manufacturing systems over the last two decades, a unified measurement approach has not been developed. To this end, we integrate two domains of machine flexibility models from the literature: operational capability-based machine flexibility and time and cost-based machine flexibility, and propose a generic model to measure machine flexibility with consideration of uncertainties in the system. Furthermore, in our approach we include part characteristics such as processing time and processing cost, the number of operations that a machine can perform, and uncertainties in demand and machine-part assignment. The resulting framework to measure machine flexibility is a two-stage model: a super efficiency Data Envelopment Analysis Model and a flexibility model. The results show that the marginal system machine flexibility does not always increase as the number of operations that a machine can perform increases, and the system machine flexibility depends on the demand uncertainty.     

A strategic decision support system framework for energy-efficient technology investments

Energy systems optimization under uncertainty is increasing in its importance due to on-going global de-regulation of the energy sector and the setting of environmental and efficiency targets which generate new multi-agent risks requiring a model-based stakeholders dialogue and new systemic regulations. This paper develops an integrated framework for decision support systems (DSS) for the optimal planning and operation of a building infrastructure under appearing systemic de-regulations and risks. The DSS relies on a new two-stage, dynamic stochastic optimization model with moving random time horizons bounded by stopping time moments. This allows to model impacts of potential extreme events and structural changes emerging from a stakeholders dialogue, which may occur at any moment of the decision making process. The stopping time moments induce endogenous risk aversion in strategic decisions in a form of dynamic VaR-type systemic risk measures dependent on the system’s structure. The DSS implementation via an algebraic modeling language (AML) provides an environment that enforces the necessary stakeholders dialogue for robust planning and operation of a building infrastructure. Such a framework allows the representation and solution of building infrastructure systems optimization problems, to be implemented at the building level to confront rising systemic economic and environmental global changes.     

Computer aided decision support system for water strategic planning in Jordan

The Nominal Group Technique and a multi-criteria decision aid software are utilised to develop a decision support system for strategic planning of water resources in Jordan. The system described is novel in that it integrates the various decision analytical management techniques in order to increase the flexibility and efficiency of the decision making process.     

Decision support for strategic energy planning: A robust optimization framework

Optimization models for long-term energy planning often feature many uncertain inputs, which can be handled using robust optimization. However, uncertainty is seldom accounted for in the energy planning practice, and robust optimization applications in this field normally consider only a few uncertain parameters. A reason for this gap between energy practice and stochastic modeling is that large-scale energy models often present features—such as multiplied uncertain parameters in the objective and many uncertainties in the constraints—which make it difficult to develop generalized and tractable robust formulations. In this paper, we address these limiting features to provide a complete robust optimization framework allowing the consideration of all uncertain parameters in energy models. We also introduce an original approach to make use of the obtained robust formulations for decision support and provide a case study of a national energy system for validation.     

A flexible multicriteria decision-making methodology to support the strategic management of Science,Technology and Innovation research funding programs

Research funding programs are a policy instrument utilized by governments to influence the innovation process. They are usually elaborated, launched and managed by research funding agencies. In order to select the most adequate research projects, agencies often rely on the peer review process.This paper introduces a methodology to support funding decisions based on the peer review process. The methodology involves the use of a multicriteria decision model to support the assessment, evaluation, prioritization and selection of applications, under a multi-step decision-making process, which fits into a strategic management cycle within the agency. The Multiattribute Value Theory, being considered under a Value Focused Thinking approach, provides a basis for the construction of the multicriteria decision model. The good practices in peer review and also a logical framework for program management are considered by the methodology.A pilot study, presented in the paper, involved a retrospective implementation of a peer review process in the context of a program launched by the Ministry for Science, Technology, Innovations and Communications and the National Council of Technological and Scientific Development, in Brazil. The methodology allowed a clear distinction of roles. The agency staff in the role of decision-makers was responsible for making value judgments on behalf of the agency. The experts, in the role of committee members and ad hoc reviewers, contributed with their expertise by providing objective assessments. Such assessments served as a basis for evaluating the applications, characterizing the possible portfolios, and can be considered as data in future program evaluation studies.     

A decision support system to manage the supply chain of sugar cane

In this work the authors present a Decision Support System (DSS) for planning daily operations in the sugar cane supply chain. The supply chain model is based on a mixed integer linear programming model. The model objective is to minimize transportation costs while assuring cane supply to the sugar mill. The model determines the fields to harvest, the cutting-loading-transport means for such operation, and the roster for each employee. The DSS has been tested under Cuban conditions but easily can be adapted to different situations updating the parameters of the model. Reported savings represent an 8 % of the fuel cost.     

An optimization-based decision support system for strategic planning in a process industry: the case of aluminium company in India

We describe how a generic multi-period optimization-based decision support system (DSS) can be used for strategic planning in process industries. The DSS is built on five fundamental elements—materials, facilities, activities, storage areas, and time periods. It requires little direct knowledge of optimization techniques to be used effectively. Results based on real data from an aluminium company in India demonstrate significant potential for improvement in profits. We conclude with a comparison of similar studies in two other process industries.     

A review of strategic mobility models supporting the defense transportation system

The complexity of military logistics and force deployment modeling requires the use of advanced computer models for analysis. The last 20 years have not only seen a concerted effort to improve the fidelity of these models, but development to improve their interconnectivity. The area of strategic mobility has received greater interest in the last decade as the U.S. Military has become more reliant on a force projection posture rather than prepositioning its forces outside the continental United States. Strategic mobility describes how forces within the continental U.S. are deployed in support missions outside the continental U.S. This posture combined with the ever shrinking military budget and force size has placed increased emphasis on the capability to efficiently deploy personnel, equipment, and support materiel. Mobility modeling is conducted at various levels of the mobility planning process. The result is a myriad of models addressing different aspects of the process. Current models addressing strategic mobility use aggregate network flow models, one-pass greedy approaches, and simple bounding techniques. This paper presents an overview of these models, their operating characteristics, and their advantages and disadvantages for mobility modeling applications.     

Product concept and prototype flexibility in manufacturing: Implications for customer satisfaction

A rapidly changing competitive landscape and dynamic customer expectations require manufacturing firms to seek flexibility in product development. Product concept flexibility (i.e., developing design options) and product prototype flexibility (i.e., creating working models) emerge as effective ways to quickly develop new products that meet competitive challenges and satisfy customer demands. Product concept flexibility enables firms to fully explore various product definitions and ideas. Product prototype flexibility allows firms to gather customers’ feedback and investigate design feasibility. Using data from 273 manufacturing firms, this research tests mediating, moderating, and additive models that relate product concept flexibility, product prototype flexibility, and customer satisfaction. The results indicate that firms with high product concept flexibility are more likely to benefit from prototype flexibility than firms with low product concept flexibility, and that product concept flexibility and product prototype flexibility act independently and additively to predict customer satisfaction.     

适合中小型制造企业的客户信用评估的研究

本在对中小型制造企业的客户管理调研基础上，建立了适合中小型制造企业的信用评估指标体系，提出了基于AHP、TOPSIS和聚类分析的客户信用评估方法，并在上海某企业进行了实践，取得了较好的效果。     

Implementation of Lean Six Sigma in small- and medium-sized manufacturing enterprises in the Netherlands

In this paper we provide an exploration and analysis of Lean Six Sigma (LSS) implementation in Dutch manufacturing/engineering small- and medium-sized enterprises (SMEs). Critical success factors (CSFs) and impeding factors are identified and analysed. Exploratory empirical evidence about LSS implementation in Dutch SMEs was collected from a survey study on Dutch SMEs. Statistical testing was applied to validate the ranking of the CSFs. To deepen insight in how organizations translate CSFs into practice and cope with impeding factors, additional in-depth qualitative information was gathered from six case studies. Linking to customer, vision and plan statement, communication and management involvement and participation are the highest ranked CSFs. Internal resistance, the availability of resources, changing business focus and lack of leadership are the strongest impeding factors. The case studies confirmed the importance of the CSFs and revealed three new CSFs: personal LSS-experience of Top management, development of the project leader's soft skills and supply chain focus. SMEs in the Netherlands make no distinct separation between lean manufacturing and Six Sigma, but rather apply both approaches intertwined.     

A dispatching rule-based approach to production scheduling in a printed circuit board manufacturing system

This paper focuses on a production-scheduling problem in a printed circuit board (PCB) manufacturing system that produces multiple product types with different due dates and different manufacturing processes. In the PCB manufacturing system, there is a number of serial workstations, and there are multiple parallel machines at each workstation. Also, setup operations are required at certain workstations or machines, and some product types have re-entrant flows. We develop new dispatching rules for scheduling at each workstation, considering the special features of PCB manufacturing. With the dispatching rules, we determine not only the start time of each lot at a machine but also the batch size of each product at each machine. Simulation experiments are carried out to test the performance of the production-scheduling method and dispatching rules devised in this study. Results show that the production-scheduling method suggested in this study performs better than methods with well-known dispatching rules and heuristic algorithms for lot sizing in terms of the total tardiness of orders.     

Formation of a strategic manufacturing and distribution network with transfer prices

We propose a profit maximization model for the decision support system of a firm that wishes to establish or rationalize a multinational manufacturing and distribution network to produce and deliver finished goods from sources to consumers. The model simultaneously evaluates all traditional location factors in a manufacturing and distribution network design problem and sets intra-firm transfer prices that take account of tax and exchange rate differentials between countries. Utilizing the generalized Benders decomposition approach, we exploit the partition between the product flow and the cash allocation (i.e., the pricing and revenue assignment) decisions in the supply chain to find near optimal model solutions. Our proposed profit maximizing strategic planning model produces intuitive results. We offer computational experiments to illustrate the potential valuable guidance the model can provide to a firm's supply chain design strategic planning process.     

Measurement of loading and operations flexibility in flexible manufacturing systems: An information-theoretic approach

An information-theoretic approach is applied for measuring the flexibility in flexible manufacturing systems (FMSs). The general relation between flexibility and entropy is discussed. The entropy for a Markovian process is obtained and then applied to closed queueing network models of FMSs to discuss loading flexibility which arises from the power to regulate the frequency of the visit of a part to different work stations. The concept of operations entropy as a measure of operations flexibility, which arises from the power to choose the work station and the corresponding operations, is introduced. The operations entropy has been decomposed into entropies within and between operations and entropies within and between groups of operations. This measure has been used to determine the next operation to be performed on a part by using the principle of least reduction of flexibility.The present paper is an improved version of the paper On measurement of flexibility in flexible manufacturing systems: An information-theoretic approach, presented at the II ORSA/TIMS Special Conference on Flexible Manufacturing Systems, held at Ann Arbor in August 1986.     

A numerical study on a nonlinear conservation law model pertaining to manufacturing system

This paper deals with a numerical scheme applied to a conservation law model of manufacturing system incorporating yield loss. Yield loss involving a singular term has been considered. Even though an explicit form of the material density in a production system can be obtained under certain assumptions, in general, it is difficult to get an explicit form of the material density. On the other hand, the singular term in a conservation law model imposes severe challenges for the numerical approximations on regular grids. Moreover, an approximate solution often converges to a wrong weak solution. A finite volume type numerical scheme has been studied. The convergence of the numerical solution towards entropy solution (in the Kruzkov sense) is proved. Numerical experiments are presented to get the overview of density distribution and outflux of the system.     

A numerical method to approximate optimal production and maintenance plan in a flexible manufacturing system

The simultaneous planning of the production and the maintenance in a flexible manufacturing system is considered in this paper. The manufacturing system is composed of one machine that produces a single product. There is a preventive maintenance plan to reduce the failure rate of the machine. This paper is different from the previous researches in this area in two separate ways. First, the failure rate of the machine is supposed to be a function of its age. Second, we assume that the demand of the manufacturing product is time dependent and its rate depends on the level of advertisement on that product. The objective is to maximize the expected discounted total profit of the firm over an infinite time horizon. In the process of finding a solution to the problem, we first characterize an optimal control by introducing a set of Hamilton–Jacobi–Bellman partial differential equations. Then we realize that under practical assumptions, this set of equations can not be solved analytically. Thus to find a suboptimal control, we approximate the original stochastic optimal control model by a discrete-time deterministic optimal control problem. Then proposing a numerical method to solve the steady state Riccati equation, we approximate a suboptimal solution to the problem.     

A Decision support system integrating AHP and MDS to predict choice

A decision support system is proposed which uses the analytic hierarchy process along with integer programming to constrain the overall choice set. Two strategies for predicting choice are then presented. The first is a single step process which uses multi-dimensional scaling. The second strategy is an iterative process which uses both multi-dimensional scaling and the analytic hierarchy process. The latter strategy is discussed in detail and an illustrative example is provided.     

HADTS: A decision technology system to support Army housing management

The Department of Army must provide its personnel with acceptable housing at minimum cost within the vicinity of military installations. To achieve these housing objectives, the Army often must enter into agreements for the longterm construction of onpost housing or the leasing of existing offpost housing. A decision support system, called HANS, has been developed to project the necessary construction or leasing.HANS had some gaps in supporting the construction and leasing decisions. This paper describes the gaps and shows how a decision technology system, called the Housing Analysis Decision Technology System (HADTS), can help Army managers to overcome the support gaps. It also overviews HADTS's benefits, challenges, and limitations.     

A principle of construction of an integrated machine manufacturing system

The problems arising in the automation of multiproduct small batch production in mechanical engineering due to necessity to ensure its high flexibility are indicated. It is shown that the automation level of such a production can be effectively increased by the organization of a group production and the part orientation of equipment. In so doing it is useful to group parts on the basis of their standard images and enrichment elements. The use of standard image concept promotes the integration of design and manufacturing and creates the prerequisites for the automation of design. The planning of group production organized on the basis of standard images and enrichment elements realizes by regrouping the parts-setting-ups matrix. The method of matrix regrouping facilitating the group production planning is proposed. The described principles of organizing the computer-aided design and manufacturing on the basis of standard images and enrichment elements have been used in constructing the integrated system KAPRI intended for pilot production with a variable range of parts.     

Minimizing support structures and trapped area in two-dimensional layered manufacturing

Algorithms are given for the two-dimensional versions of optimization problems arising in layered manufacturing, where a polygonal object is built by slicing its CAD model and manufacturing the slices successively. The problems considered are minimizing (i) the contact-length between the supports and the manufactured object, (ii) the area of the support structures used, and (iii) the area of the so-called trapped regions—factors that affect the cost and quality of the process.