Fuzzy multiple-goal programming for analysing outsourcing cost-effectiveness in hi-tech manufacturing

Given high-tech industry trends such as limited production, diverse model range, short product life cycle, and high customer responsiveness, issues related to recognitive core vs. non-core operations in internal vs. external environments are crucial in hi-tech production systems planning. This work elucidates the relationship between capacity planning and suppliers with a focus on quantity allocation, manufacturing quantity, capacity limit, warehouse space, and time period for hi-tech production planning. A fuzzy multiple-goal programming approach is adopted to model total cost, holding cost, and rework cost in order to analyse the relative cost-effectiveness of different factors. The proposed model was examined via the fuzzy analysis of its application to an actual building-integrated photovoltaic (BIPV) manufacturer with variable characteristics. The proposed model of cost-effectiveness accommodates variables such as multiple components, quality, and responsiveness, it integrates multi-stage functions, and a specific implementation is demonstrated. Various scenarios are designed to analyse the transaction options for outsourcing under combined schemes. The analytical results in this study can help decision makers to systematically analyse the cost effectiveness of outsourcing during capacity planning in practical applications.     

Use of the manufacturing system design decomposition for comparative analysis and effective design of production systems

The focus of this paper is on the use of the Manufacturing System Design Decomposition (MSDD) to make effective cost and production system design decisions. A comparative study is conducted to illustrate how and why the total cost is reduced when the functional requirements defined by the MSDD are achieved. The ultimate goal of this research was to advance manufacturing and production system development to being guided by engineering science and design rather than the common practice of duplicating another person’s or entity’s notion of the best physical implementation.     

Intelligent decision support system for the adaptive control of a flexible manufacturing system with machine and tool flexibility

This paper describes an intelligent decision support system (IDSS) for real time control of a flexible manufacturing system (FMS). The controller is capable of classifying symptoms in developing the control policies on FMSs with flexibility in operation assignment and scheduling of multi-purpose machining centres which have different tools with their own efficiency. The proposed system is implemented by coupling of rule-based IDSS, simulation block and centralised simulation optimiser for elicitation of shop floor control knowledge. This posteriori adaptive controller uses a new bilateral mechanism in simulation optimiser block for offline training of IDSS based on multi-performance criteria simulation optimisation. The proposed intelligent controller receives online information of the FMS current state and trigger appropriate control rule within real-time simulation data exchange. Finally the FMS intelligent controller is validated by a benchmark test problem. Application of this adaptive controller showed that it could be an effective approach for real time control of various flexible manufacturing systems.     

A spread-sheet model for efficient production and scheduling of a manufacturing line/cell

In this paper we develop an efficient spread-sheet production planning/scheduling model for a resource-constraint production line or a manufacturing cell that produces several products but one at a time with significant changeover time and changeover cost. There are also management and physical constraints related to the operating hours, production capacity and amount of inventory allowed. The production line/cell supplies several products to customers who pull the products according to their own operating policy (working hours) that may be different from manufacture's operating hours. We also show several real-world applications and highlight the benefits and merits of the model.     

A bi-level constraint-oriented outsourcing framework for orchestration of an ERP system

Outputs of each enterprise resource planning (ERP) process in an ERP system could constraint outputs of the next ERP processes. Therefore, it is necessary to determine the ability of ERP processes to support the orchestration of an ERP system. This paper presents a bi-level constraint-oriented outsourcing framework to identify any ERP process that effects on the orchestration of an ERP system. The contribution of the proposed bi-level constraint-oriented outsourcing framework for orchestration of ERP is twofold: (1) it develops the traditional constraints management from a crisp single-criteria environment to a fuzzy multi-criteria environment; and (2) it develops a linear programming technique for multidimensional analysis of preference (LINMAP) model to a fuzzy group bi-level LINMAP model. A case study demonstrates the applicability of the proposed constraint-oriented outsourcing framework for orchestration of ERP modules and processes.     

Shipyard production cost structure optimisation model related to product type

Establishing a shipbuilding production cost structure is a fundamental management activity, concerning materials and fabrication. Shipyards compete in world market niches regarding vessel type and dimensions. Therefore, the vessel's market price has a tremendous influence on the shipyard's determination of the price of the vessel offered to buyers. For this reason, shipyard management is forced to concentrate its efforts on production cost structure optimisation in order to achieve the goal of a profitable shipyard. In this paper, a computer-integrated cost structure optimisation model for defining an optimal and profitable vessel production cost structure is presented. Statistical analysis of the data was performed for a sample of tankers, built in selected shipyards. Probabilistic theory was applied and several results, such as expectation for aggregate figures, are presented. Such a tool for obtaining an optimal production cost structure enables shipyard management to carry out more effective decision-making, and also better cost control within model parameters. Furthermore, dynamical control of costing figures for the whole shipbuilding process is possible and has a significant influence on the final results. The mathematical model for achieving an optimal structure of the production costs was verified and tested against a real example of the construction of tankers.     

Alternative production strategies based on the comparison of additive and traditional manufacturing technologies

Additive manufacturing technology has been evolving for several years. New material options, better processing speeds and greater autonomy are some of the characteristics of this technology that are still under research. However, in its current state, many commercially available 3D printers are competing with traditional manufacturing techniques in the fabrication of end-use products. In this paper, different additive manufacturing technologies are compared with injection moulding in a real-world case study. The comparison is conducted in terms of lead time and total production cost. From the case under study, it becomes obvious that none of the additive manufacturing technologies examined is yet able to practically replace injection moulding for medium- and high production volumes. However, when considering low-volume production, both rapid tooling and additive manufacturing may offer an alternative that could result into shorter lead times and decreased total production costs. In addition, the introduction of Additive Manufacturing in a producer’s production portfolio can increase flexibility, reduce warehousing costs and assist the company towards the adoption of a mass customisation business strategy.     

A simulated annealing algorithm based on a closed loop layout for facility layout design in flexible manufacturing systems

Facility layout design problems in flexible manufacturing systems (FMS) differ from traditional facility design problems and are more difficult to solve because there are more constraints that must be considered (i.e., cell shape, cell orientation, pick-up and drop-off point positions). The focus of this paper is on the closed loop type layout, which is based on a predetermined layout pattern. This layout pattern is commonly found in manufacturing settings since it requires a simplified material handling system configuration and since it facilitates a modular and expandable layout structure. The open-field type layout problem, where there is no predetermined layout pattern, may potentially have a more efficient configuration, since there are fewer restrictions. However, this problem is more difficult to solve and may result in configurations that are not desirable due to the lack of structure or modularity. The procedure developed in this paper improves the efficiency of the closed loop configuration by changing the rectangular shape of the loop to different sizes. In many cases, the resulting closed loop layout proves to be as efficient as the open field layout. A simulated annealing procedure (SA-CL) is used to search for the configuration that minimizes the total material handling costs. A comparison of the results with existing methods indicates that, based on solution quality and computational time, the SA-CL offers a favourable alternative for efficient layout design.     

Integrated predictive maintenance strategy for manufacturing systems by combining quality control and mission reliability analysis

Predictive maintenance (PdM) is an effective means to eliminate potential failures, ensure stable equipment operation and improve the mission reliability of manufacturing systems and the quality of products, which is the premise of intelligent manufacturing. Therefore, an integrated PdM strategy considering product quality level and mission reliability state is proposed regarding the intelligent manufacturing philosophy of ‘prediction and manufacturing’. First, the key process variables are identified and integrated into the evaluation of the equipment degradation state. Second, the quality deviation index is defined to describe the quality of the product quantitatively according to the co-effect of manufacturing system component reliability and product quality in the quality–reliability chain. Third, to achieve changeable production task demands, mission reliability is defined to characterise the equipment production states comprehensively. The optimal integrated PdM strategy, which combines quality control and mission reliability analysis, is obtained by minimising the total cost. Finally, a case study on decision-making with the integrated PdM strategy for a cylinder head manufacturing system is presented to validate the effectiveness of the proposed method. The final results shows that proposed method achieves approximately 26.02 and 20.54% cost improvement over periodic preventive maintenance and conventional condition-based maintenance respectively.     

A new heuristic for integrated process planning and scheduling in reconfigurable manufacturing systems

Integrated process planning and scheduling (IPPS) is a manufacturing strategy that considers process planning and scheduling as an integrated function rather than two separated functions performed sequentially. In this paper, we propose a new heuristic to IPPS problem for reconfigurable manufacturing systems (RMS). An RMS consists mainly of reconfigurable machine tools (RMTs), each with multiple configurations, and can perform different operations with different capacities. The proposed heuristic takes into account the multi-configuration nature of machines to integrate both process planning and scheduling. To illustrate the applicability and the efficiency of the proposed heuristic, a numerical example is presented where the heuristic is compared to a classical sequential process planning and scheduling strategy using a discrete-event simulation framework. The results show an advantage of the proposed heuristic over the sequential process planning and scheduling strategy.     

Optimal decision of an economic production quantity model for imperfect manufacturing under hybrid maintenance policy with shortages and partial backlogging

Considering the characteristics of the stochastic shift of the machine state and the uncertainty of the product quality of production, in this paper, we develop an optimisation decision of economic production quantity model for an imperfect manufacturing system under hybrid maintenance policy with shortages and partial backlogging. We assume that the production process is imperfect stemming from the machine reliability and the probability of out-of-control, a hybrid maintenance policy combined of emergency maintenance and preventive maintenance is executed during each production run. Three decision models based on the scenarios of machine breakdown and repair time are developed. The optimal production quantity and maintenance inspection number during each production run are solved with minimising the expected average cost of the system. Numerical examples are used to demonstrate the effectiveness and feasibility of the model. Sensitivity analysis is conducted to analyse the impacts of key parameters on the optimal decision. Some implications related to the effective and economical execution of maintenance policy for practitioners are derived.     

A robust optimisation model for hybrid remanufacturing and manufacturing systems under uncertain return quality and market demand

In remanufacturing research, most researchers predominantly emphasised on the recovery of whole product (core) rather than at the component level due to its complexity. In contrast, this paper addresses the challenges to focus on remanufacturing through component recovery, so as to solve production planning problems of hybrid remanufacturing and manufacturing systems. To deal with the uncertainties of quality and quantity of product returns, the processing time of remanufacturing, remanufacturing costs, as well as market demands, a robust optimisation model was developed in this research and a case study was used to evaluate its effectiveness and efficiency. To strengthen this research, a sensitivity analysis of the uncertain parameters and the original equipment manufacturer’s (OEM’s) pricing strategy was also conducted. The research finding shows that the market demand volatility leads to a significant increase in the under fulfilment and a reduction in OEM’s profit. On the other hand, recovery cost reduction, as endogenous cost saving, encourages the OEM to produce more remanufactured products with the increase in market demand. Furthermore, the OEM may risk profit loss if they raise the price of new products, and inversely, they could gain more if the price of remanufactured products is raised.     

基于精益设计的生产能力分析与现场物流改善

结合精益设计的思想并应用仿真分析,提出了一种生产流程精益设计的方法。该方法通过仿真分析了系统的生产能力、车间布局和物流,以及整个系统的性能。根据仿真结果,可以选择其中最佳的方案使得生产能力与市场需求相匹配,车间布局和物流得到优化,对车间空间需求减少。一个例子用来说明该方法的应用和效果。     

模具企业生产调度管理系统的研究

为适应模具企业新的生产方式,本文提出了一种结合合同网协议、GPGP协同机制和TAEMS任务描述语言的任务分配和调度方法,并建立层/级结构的整体框架和各级调度策略.该方法从整体的角度分析问题,提高了调度结果的一致性和优化性.初步的验证表明该方法是有效的.     

A hybrid multi-stage predictive model for supply chain network collapse recovery analysis: a practical framework for effective supply chain network continuity management

In this paper, we present a multi-stage hybrid model for analysing a supply chain network (SCN) collapse recovery possibility. In the first stage of the model, we analyse the ability of an SCN to fulfil its customers required due date (RDD). As soon as the SCN defaults to timely fulfil their customers RDD, the second stage of the model is triggered to measure the collapse recovery possibility (CRP) of the SCN. Then, we calculate the final collapse recovery possibility (FCRP) of the SCN. Since the operation times, customer demand and external supply of raw material are uncertain, we use fuzzy triangular numbers to estimate the value of foregoing parameters. Consequently, we employ fuzzy program evaluation and review technique (FPERT) to calculate the completion time of SCN operations. In the third stage, for the critical elements of the SCN obtained from FPERT, the SC simulator is developed to provide a dynamic view of the SC and assesses the impact of decisions recommended by the SC fuzzy models on SC performance. Moreover, an empirical example is presented to validate the effectiveness of the proposed model. Finally, we conduct sensitivity analysis on the parameters employed in the model to analyse the behaviour of each parameter.