A heuristic for formulating within-plant manufacturing focus

The concept of manufacturing focus suggests that each plant is assigned a unique set of manufacturing tasks derived from the firm's competitive strategy. Many empirical studies have verified the importance and benefits of manufacturing focus in enhancing a firm's competence in the market. Nonetheless there is no methodology offered for designing such a manufacturing system with considerations of resource requirements although the need has been recognized. In this study, we propose a methodology that can help managers arrive at a manufacturing focus design within a plant. Because of the large size and nonlinear nature of the problem, a heuristic solution is proposed. The heuristic translates the strategic concept of competitive priorities into management parameters, thereby allowing incorporation of market factors into manufacturing process design. Experimental results show that the proposed methodology offers managers the opportunity to generate and assess alternative focus designs which are otherwise unavailable. The use of the heuristic is straightforward in practical situations and should greatly facilitate the achievement of manufacturing focus with minimal resource requirements. Overall, this research provides an analytical framework for further research in focused manufacturing.     

A time-based quantitative approach for selecting lean strategies for manufacturing organisations

Lean strategies have been developed to eliminate or reduce waste and thus improve operational efficiency in a manufacturing environment. However, in practice, manufacturers encounter difficulties to select appropriate lean strategies within their resource constraints and to quantitatively evaluate the perceived value of manufacturing waste reduction. This paper presents a methodology developed to quantitatively evaluate the contribution of lean strategies selected to reduce manufacturing wastes within the manufacturers’ resource (time) constraints. A mathematical model has been developed for evaluating the perceived value of lean strategies to manufacturing waste reduction and a step-by-step methodology is provided for selecting appropriate lean strategies to improve the manufacturing performance within their resource constraints. A computer program is developed in MATLAB for finding the optimum solution. With the help of a case study, the proposed methodology and developed model has been validated. A ‘lean strategy-wastes’ correlation matrix has been proposed to establish the relationship between the manufacturing wastes and lean strategies. Using the correlation matrix and applying the proposed methodology and developed mathematical model, authors came out with optimised perceived value of reduction of a manufacturer's wastes by implementing appropriate lean strategies within a manufacturer's resources constraints. Results also demonstrate that the perceived value of reduction of manufacturing wastes can significantly be changed based on policies and product strategy taken by a manufacturer. The proposed methodology can also be used in dynamic situations by changing the input in the programme developed in MATLAB. By identifying appropriate lean strategies for specific manufacturing wastes, a manufacturer can better prioritise implementation efforts and resources to maximise the success of implementing lean strategies in their organisation.     

Quantity discount decisions under conditions of multiple items,multiple suppliers and resource limitations

This research considers quantity discount procedures under conditions of multiple items, resource limitations and multiple suppliers. This is a very complex problem that has not yet been addressed in the literature. In this paper we offer an efficient heuristic programming procedure for evaluating alternative discount schedules. Moreover we use an example problem to test the suggested procedure. The results offer several encouraging findings for managers facing this impressive problem.     

面向大批量定制的可重组自动化装备

在大批量定制正在成为２１世纪制造业的主流生产模式的背景下,对国内外可重组自动化装备的研究现状和国内装备制造业存在的问题进行了分析,提出了发展面向大批量定制的可重组自动化装备的设想,包括面向大批量定制的可重组自动化装备发展战略和设计方法学的研究、开放式数控系统研究、面向大批量定制的可重组机床的可重组制造系统的研究等．     

Manufacturing strategies for the ecosystem-based manufacturing system in the context of 3D printing

This paper aims to investigate the manufacturing strategies for the manufacturing systems in the context of 3D printing, referring to ecosystem-based manufacturing systems, rather than firm-based and network-based ones. A case study approach was adopted for this research, as the data was mainly collected via semi-structured interviews with staff members of companies in China. Besides the elements of strategic choices and manufacturing capabilities identified in the extant literature, this research verified three additional strategic choice elements (functional role, platform and solution) and identified two factors (platform openness and solution diversity) to classify an ecosystem-based manufacturing system. Meanwhile, four manufacturing capabilities of the ecosystem-based manufacturing system have been identified: collaborative manufacturing flexibility, rapid thriftiness ability, self-customisation and co-evolved design capability. The research results contribute to the area of manufacturing strategy via expanding its view from the firm and network levels to the ecosystem level. Meanwhile, the research results present operations managers with an understanding of the strategic choices and manufacturing capabilities of an ecosystem-based manufacturing system in the context of 3D printing.     

Lean tool selection in a die casting unit: a fuzzy-based decision support heuristic

Lean manufacturing philosophy asks for elimination of wastes hidden in the manufacturing system by focusing on product value stream and eliminating non-value adding activities through continuous improvement efforts. Value stream mapping methodology is subjected to principles of continuous improvement in order to improve the productivity of the process and quality of the product. It provides various tools for data collection and analysis, and identifies the wastes occurring in different stages of manufacturing process. The role of value stream mapping is very important in the identification and subsequently reduction of the wastes. To select the detailed mapping tools for the identification of waste at micro level is a complex decision making problem. In this paper, a case study related to a die casting unit has been taken. A hierarchy related to the decision problem has been developed to select the value stream mapping tools. Here, a fuzzy logic based multi-preference, multi-criteria, and multi-person decision making heuristic has been developed to solve a problem pertaining to above case study. The proposed methodology enjoys logical support from existing decision making tools and pertinently maps the inside details of the underlying problem.     

A similarity score-based two-phase heuristic approach to solve the dynamic cellular facility layout for manufacturing systems

The dynamic cellular facility layout problem (DCFLP) is a well-known NP-hard problem. It has been estimated that the efficient design of DCFLP reduces the manufacturing cost of products by maintaining the minimum material flow among all machines in all cells, as the material flow contributes around 10–30% of the total product cost. However, being NP hard, solving the DCFLP optimally is very difficult in reasonable time. Therefore, this article proposes a novel similarity score-based two-phase heuristic approach to solve the DCFLP optimally considering multiple products in multiple times to be manufactured in the manufacturing layout. In the first phase of the proposed heuristic, a machine–cell cluster is created based on similarity scores between machines. This is provided as an input to the second phase to minimize inter/intracell material handling costs and rearrangement costs over the entire planning period. The solution methodology of the proposed approach is demonstrated. To show the efficiency of the two-phase heuristic approach, 21 instances are generated and solved using the optimization software package LINGO. The results show that the proposed approach can optimally solve the DCFLP in reasonable time.     

An ant colony optimisation algorithm for scheduling in agile manufacturing

Producing customised products in a short time at low cost is one of the goals of agile manufacturing. To achieve this goal an assembly-driven differentiation strategy has been proposed in the agile manufacturing literature. In this paper, we address a manufacturing system that applies the assembly-driven differentiation strategy. The system consists of machining and assembly stages, where there is a single machine at the machining stage and multiple identical assembly stations at the assembly stage. An ant colony optimisation (ACO) algorithm is developed for solving the scheduling problem of determining the sequence of parts to be produced in the system so as to minimise the maximum completion time (or makespan). The ACO algorithm uses a new dispatching rule as the heuristic desirability and variable neighbourhood search as the local search to make it more efficient and effective. To evaluate the performance of heuristic algorithms, a branch-and-bound procedure is proposed for deriving the optimal solution to the problem. Computational results show that the proposed ACO algorithm is superior to the existing algorithm, not only improving the performance but also decreasing the computation time.     

A multiobjective topology optimization approach for cost and time minimization in additive manufacturing

The ever-present drive for increasingly high-performance designs realized on shorter timelines has fostered the need for computational design generation tools such as topology optimization. However, topology optimization has always posed the challenge of generating difficult, if not impossible to manufacture designs. The recent proliferation of additive manufacturing technologies provides a solution to this challenge. The integration of these technologies undoubtedly has the potential for significant impact in the world of mechanical design and engineering. This work presents a new methodology which mathematically considers additive manufacturing cost and build time alongside the structural performance of a component during the topology optimization procedure. Two geometric factors, namely, the surface area and support volume required for the design, are found to correlate to cost and build time and are controlled through the topology optimization procedure. A novel methodology to consider each of these factors dynamically during the topology optimization procedure is presented. The methodology, based largely on the use of the spatial gradient of the density field, is developed in such a way that it does not leverage the finite element discretization scheme. This work investigates a problem that has not yet been explored in the literature: direct minimization of support material volume in density-based topology optimization. The entire methodology is formulated in a smooth and differentiable manner, and the sensitivity expressions required by gradient based optimization solvers are presented. A series of example problems are provided to demonstrate the efficacy of the proposed methodology.     

Tabu search-based algorithm for the TOC product mix decision

The theory of constraints (TOC) is a management philosophy that maximizes profits in a manufacturing plant with a demonstrated bottleneck. The product mix decision is one application of TOC that involves determination of the quantity and the identification of each product to produce. However, the original TOC heuristic is considered to produce unrealizable solution when a manufacturing plant has multiple resource constraints. This paper presents a tabu search-based TOC product mix heuristic to identify optimal or near optimal product mix for small problem instances under conditions where the original TOC heuristic failed. The tabu search-based TOC product mix heuristic is further used to solve large problem instances typical of practical manufacturing scenario. The experimental results for small to medium size problem show that the tabu search-based TOC heuristic compares favourably with those of optimal methods. Large size problems for which optimal methods have not been established in terms of feasibility in computation times were also solved in reasonable times with good quality solutions, thus confirming that the proposed approach is appropriate for adoption by production planners for the product mix problem in the manufacturing industry.     

Analysis and solution to the single-level batch production smoothing problem

Many companies use mixed-model production systems running under the Just-in-Time philosophy in order to efficiently meet customer demands for a variety of products. Such systems require demand be stable and production sequence be leveled. The production smoothing problem aims at finding level schedules in which the appearances of products are dispersed over the horizon as uniformly as possible. In this paper, the production smoothing problem is extended to a more general manufacturing environment where a single machine can be identified as either the final or the bottleneck stage of the system and products may have arbitrary non-zero setup and processing time requirements on this single machine. An optimization model is built for the problem and a two phase solution methodology is developed. The first phase problem is shown to be NP-hard and a parametric heuristic procedure is proposed for its solution. In contrast, the second phase problem is shown to be efficiently solvable and currently available solution methods are adopted from the literature. A computational study is designed to test the proposed two phase solution methodology and also the parametric heuristic procedure. Computational results show that the proposed two phase solution methodology enables effective and efficient control of the studied manufacturing system, and the heuristic procedure developed for the first phase problem is time efficient and promises near optimal solutions for a variety of test instances.     

Managing lean manufacturing in material handling operations

The problem addressed by this research is to implement lean manufacturing in a material handling system of a petroleum drill bit manufacturing company. Lean manufacturing has been mandated by higher level management as a tool to be used in waste reduction. Operational group must define the objectives of lean manufacturing and deploy the tools to specific work cells. A methodology that provides operational group with a tool to assist in defining the objectives of lean manufacturing is developed. A case study is used to demonstrate the lean implementation in material handling operations.     

Design for manufacturing: application of collaborative multidisciplinary decision-making methodology

Design for manufacturing is often difficult for mechanical parts, since significant manufacturing knowledge is required to adjust part designs for manufacturability. The traditional trial-and-error approach usually leads to expensive iterations and compromises the quality of the final design. The authors believe the appropriate way to handle product design for manufacturing problems is not to formulate a large design problem that exhaustively incorporates design and manufacturing issues, but to separate the design and manufacturing activities and provide support for collaboration between engineering teams. In this article, the Collaborative Multidisciplinary Decision-making Methodology is used to solve a product design and manufacturing problem. First, the compromise Decision Support Problem is used as a mathematical model of each engineering teams’ design decisions and as a medium for information exchange. Second, game-theoretic principles are employed to resolve couplings or interactions between the teams’ decisions. Third, design-capability indices are used to maintain design freedom at the early stages of product realization in order to accommodate unexpected downstream design changes. A plastic robot-arm design and manufacturing scenario is presented to demonstrate the application of this methodology and its effectiveness for solving a complex design for manufacturing problem in a streamlined manner, with minimal expensive iterations.     

A methodology for determining auxiliary and value-added electricity in manufacturing machines

A methodology was developed that accurately and flexibly determines the auxiliary (AU) and value-added electricity in manufacturing operations. A tool was developed for production engineers which allows for the verification of machine efficiency in relation to their energy consumption. Historical production and electricity consumption data were collected for a period of three months from four different machines in a value stream at a manufacturing facility. The data were examined using a methodology based on statistical analysis of the historical data collected and were verified using heuristic machines profiles. Results showed AU electricity consumption varied between 10 and 26% per machine. When weekend data (non-productive periods) were excluded from calculations, AU electricity consumption reduced. Past work focuses on optimising single machine, and the quantification of wasted electricity is not always clear. This research work can be applied to one or more machines, and to single or multiple products passing through the same machine. It places particular attention to AU electricity since potential energy and cost reduction of up to 20% could be achieved. Hence, this work can aid in developing key performance indicators to measure energy usage in manufacturing operations, particularly focused towards reducing AU electricity consumption.     

A similarity coefficient measure and machine-parts grouping in cellular manufacturing systems

For more than three decades, similarity coefficient measures one of the important tools for solving group technology problems have gained the attention of the research community in cellular manufacturing systems. A new similarity coefficient measure that uses a set of important characteristic properties for grouping is developed here for use as an intermediate tool to form cohesive cells. A mathematical model that uses this similarity coefficient for optimally solving the cell-formation problems in cellular manufacturing is developed. A heuristic procedure that improves the optimal methodology in term of solution capability of the large instances is devised for an efficient solution. Both the optimal methodology and the heuristic are applied to some well-known problems from literature to compare the grouping efficiencies. The similarity coefficient and the solution methodologies developed are able to solve the cell formation problems efficiently.     

A conceptual framework for the ubiquitous factory

To cope with today's industrial demands requiring (1) coverage of the whole product life cycle, (2) environmentally conscious manufacturing, (3) competitive sustainability manufacturing, etc., a new manufacturing paradigm should be developed. In this paper, we develop a conceptual framework for a new paradigm called ubiquitous factory (u-Factory) by applying ubiquitous computing technology to the manufacturing system. The u-Factory is based on our previously developed paradigm, called UbiDMR [1], meaning product design, manufacturing, and recycling via ubiquitous computing technology. The essence of u-Factory can be represented by three key phrases: (1) information transparency, (2) autonomous control, and (3) sustainable manufacturing. This paper comprises two parts. In the first part, we show the derivation procedure for the framework of the u-Factory using problem analysis of the current manufacturing system, design consideration and derivation of the architecture for the ubiquitous factory. In the second part, to demonstrate the validity and impact of the derived architecture, we develop the TO-BE model for manufacturing resource management. This is followed by a comparison with the AS-IS model.     

A mathematical model and a heuristic approach for design of the hybrid manufacturing systems to facilitate one-piece flow

One-piece flow is a design rule that entails production in manufacturing cells on a ‘make one, check one, and move-on one’ basis (Black, J.T., 2007. Design rules for implementing Toyota Production System. International Journal of Production Research, 45 (16), 3639–3664), which reduces manufacturing lead time significantly. This paper proposes a sequential methodology comprised of a mathematical model and a heuristic approach (HA) for the design of a hybrid cellular manufacturing system (HMS), to facilitate one-piece flow practice. The mathematical model is employed in the cases of small- and medium-sized problems, and it attempts to minimise the total number of exceptional operations, while considering machine capacities and alternative machines. The machine-part matrix achieved by the mathematical model is input into the flow line design stage of the HA, where backflow within the cells is eliminated. However, for industrial problems, the proposed HA is utilised. After the formation of the cells by clustering, the HA attempts to eliminate exceptional operations of a given cellular configuration together with a functional structure by employing alternative machines, based on the decision rules developed. Later, unidirectional flow within the cells is achieved and the capacity and budget constraints are satisfied. A medium-sized problem is solved by using both of the approaches, namely, the model integrated with the flow-line design stage of the HA and the complete HA. The results are discussed and the limitations are explained.     

Minimising total completion time on single-machine scheduling with new integrated maintenance activities

A single-machine scheduling problem with new maintenance activities is examined in this paper. In the scheduling literature, it is often assumed that the interval between maintenance activities is fixed or within a specified time frame. However, this assumption may not hold true in many real-world situations, such as the maintenance activities in wafer manufacturing of semiconductor. Before the wafer manufacturing process starts, it is imperative that the wafers go through a number of cleaning operations to avoid contamination. Using a cleaning agent as the main material of wafer cleaning, the contamination will be dissolved and removed from wafer surface. In case of contamination being accumulated substantial and going beyond a permitted value, the cleaning agent is highly likely to damage the wafer surfaces. Thus, the interval between maintenance activities in the wafer manufacturing process is deemed irregular. The objective function of the proposed problem is to minimise total completion time. Addressing the problem, a binary integer programming model is formulated in this paper. Furthermore, with the research problem being NP-hard, a heuristic based on two special properties is proposed to address the problem. To evaluate and validate the proposed heuristic, a new lower bound is further developed. Extensive experiments have been conducted showing that the proposed heuristic efficiently yields a near-optimal solution with an average percentage error of 15.4 from lower bound.     

Theory and practice of manufacturing strategy

This paper first proposes a methodology for manufacturing strategy development based on a critical review of the theory of manufacturing strategy. The methodology captures the essential factors that must be considered, and the steps that must be taken, by a firm attempting to design a viable manufacturing strategy. An exploratory study of the process of formulating and implementing manufacturing strategy practised by three firms is conducted. Their experiences in the manufacturing strategy process are reported and analysed. While the practice of each firm is different, the process of manufacturing strategy formulation seems to be in line with the conceptual models discussed in the literature. Our findings offer some evidence that manufacturing is slowly shedding its image as the ‘missing link’ in corporate strategy. While managers of the studied firms are fully aware of the competitive advantages that manufacturing can provide, they are not totally committed to articulating a manufacturing strategy because of concerns about its successful implementation. It is proposed that further research on manufacturing strategy focus on such implementation issues as the infrastructure, corporate culture, performance measurements, decision-making and managerial styles.