Optimal control of an unreliable machine using fuzzy-logic control: from design to implementation

In this paper, the development, implementation and validation of fuzzy logic to control an unreliable machine in manufacturing systems are presented. The fuzzy-logic controller developed in this context is based on the optimal control policy using hedging-point methodology. The fuzzy-logic controller has two-subsets of fuzzy-logic controls. The first provides a decision whether the system should produce part at make-to-stock or at make-to-order mode. The decision provided by the first fuzzy-logic control is then used by the second fuzzy-logic control to specify at what production rate the part should be produced. Simulation and implementation have been performed by controlling an unreliable machine using the developed fuzzy-logic controller. Then, the simulation results are compared with the simulation results given by the optimal control policy (hedging-point methodology). The results show that the performance of the developed fuzzy logic outperforms and is more precise than the hedging-point method under certain conditions.     

A fuzzy QFD program modelling approach using the method of imprecision

The use of quality function deployment (QFD) to aid decision making in product planning has gained extensive international attention, but current QFD approaches are unable to cope with complex product planning (CPP) characterized by involving multiple engineering characteristics (ECs) associated with significant uncertainty. To tackle this difficulty, in this paper, fuzzy set theory is embedded into a QFD framework and a novel fuzzy QFD program modelling approach to CPP is proposed to optimize the values of ECs by taking the design uncertainty and financial considerations into account. In the proposed methodology, fuzzy set theory is used to account for design uncertainty, and the method of imprecision (MoI) is employed to perform multiple-attribute synthesis to generate a family of synthesis strategies by varying the value of s, which indicates the different compensation levels among ECs. The proposed methodology will allow QFD practitioners to control the distribution of their development budget by presetting the value of s to determine the compensation levels among ECs. An illustrative example of the quality improvement of the design of a motor car is provided to demonstrate the application and performance of the modelling approach.     

Functional characterisation of mechanical joints to facilitate its selection during the design of open architecture products

New trends in product design require the use of modularity as key feature aimed to improve functional performance and the generation of open architecture products. For mechanical systems, one of the challenges during early design stages of these products involves the proper selection of joining methods among their constructive components. A robust joint selection process must consider product requirements, life cycle analysis and eventual procedures for assembly and disassembly. However, the general approach towards a Design-for-Assembly (DFA)/Design-for-Disassembly (DFD) only considers design, manufacturing and in some cases final disposal stage. Additionally, most of the works found in the literature are merely focused on assembly operations, disregarding economic and environmental benefits from optimising disassembly complexity. Herein, a functional characterisation of mechanical joint methods for the assembly and disassembly activities that take place throughout the product life cycle is proposed, focusing on open architecture products. Additionally, a classification of joining methods, a joint complexity metric valuation and a selection process are proposed for the conceptual design stage. The approach integrates both DFA and DFD principles in a formal methodology. The proposed selection roadmap can be implemented to increase product sustainability positively regarding resources optimisation, operational time and costs in reuse, remanufacturing and recycling tasks.     

Determining design requirements in QFD using fuzzy mixed-integer goal programming: application of a decision support system

In product development, the identification of critical design requirements (DRs) is key to satisfying customer needs because it helps produce more successful products in a shorter time. Quality function deployment (QFD) is a tool used in product development to systematically determine the DRs so as to attain higher customer satisfaction. In the QFD process, the simultaneous optimisation of more than one conflicting objective is generally required. However, it is very difficult for decision makers to determine the goal value of each objective in imprecise and uncertain environments. In order to overcome this problem, the present study proposes a fuzzy mixed-integer goal programming model that determines a combination of optimal DR values. Different from the existing fuzzy goal programming models, the values of the DRs in the proposed model are taken as discrete. Finally, a new Decision Support System is developed. The new system integrates QFD and mathematical programming, enabling the design team to effectively compare product design alternatives and make product development easier and faster. The proposed methodology is illustrated using a real-world application in the Turkish white goods industry.     

The application of workload control in assembly job shops: an assessment by simulation

Workload control (WLC) is a production planning and control concept developed to meet the needs of small- and medium-sized make-to-order companies, where a job shop configuration is common. Although simulation has shown WLC can improve job shop performance, field researchers have encountered significant implementation challenges. One of the most notable challenges is the presence of ‘assembly job shops’ where product structures are more complex than typically modelled in simulation and where the final product consists of several sub-assemblies (or work orders) which have to be co-ordinated. WLC theory has not been developed sufficiently to handle such contexts, and the available literature on assembly job shops is limited. In response, this paper extends the applicability of WLC to assembly job shops by determining the best combination of: (i) WLC due date (DD) setting policy, (ii) release method and (iii) policy for coordinating the progress of work orders. When DDs are predominantly set by the company, the DD setting policy should play the leading role while the role of order release should be limited and the progress of work orders should not be co-ordinated in accordance with the DD of the final product. But when DDs are predominantly specified by customers, the importance of order release as a second workload balancing mechanism increases and work orders should be coordinated by backward scheduling from the DD of the final product. Results indicate that WLC can improve performance in assembly job shops and outperform alternative control policies. Future research should implement these findings in practice.     

A novel approach to include sustainability concepts in classical DFMA methodology for sheet metal enclosure devices

Nowadays sustainable design is a mandatory requirement in the product development process. For this reason, design methodologies are addressed to establish a close relationship between environmental, social and economic impact indicators and product features from early design stages, especially in those features related to its manufacturing. In this paper, the design for manufacturing and assembly—DFMA methodology is adapted to sheet metal enclosure devices, integrating functional and component relationships to minimize particular sustainability indicators such as energy consumption, carbon footprint, number of parts, required amount of material, assembly time and manufacturing costs. Savings with the proposed method are achieved following specific sub-tasks oriented to define new simplified product components, considering changes in manufacturing processes and re-defining mechanical connections between parts. Traditional DFMA approaches consider manufacturing and assembly issues related to a reduction of product complexity and economic savings. The proposed method aims to examine the benefits in life cycle stages such as raw material consumption, service, maintenance, upgrading and end of life—EOL. The methodology is validated through a redesign of a sheet metal industrial clock, in which the sustainability impacts are calculated from a comparison of an existent product vs. a new product development. The implementation of the method in the case study demonstrate reductions of more than 25% in product mass, consumed energy and CO₂ footprint, and more than 50% in theoretical assembly time and product complexity. Sustainability indicators of the proposed method are selected from literature analysis and taking into account attributes of sheet metal enclosure devices.     

Fuzzy expected value modelling approach for determining target values of engineering characteristics in QFD

Quality function deployment (QFD) is a planning and problem-solving tool that is renowned for translating customer requirements into the technical attributes of a product. To deal with the imprecise elements in the development process, fuzzy set theory is incorporated into QFD methodology. A novel fuzzy expected value operator approach is proposed in this paper to model the QFD process in a fuzzy environment, and two fuzzy expected value models are established to determine the target values of engineering characteristics in handling different practical design scenarios. Analogous to stochastic programming, the underlying philosophy in the proposed approach is based on selecting the decision with maximum expected returns. Furthermore, the proposed approach considers not only the inherent fuzziness in the relationships between customer requirements and engineering characteristics, but also the correlation among engineering characteristics. These two kinds of fuzzy relationships are aggregated to give the fuzzy importance of individual engineering characteristics. Finally, an example of a quality improvement problem of a motor car design is given to demonstrate the application and performance of the proposed modelling approach.     

Operator assignment with cell loading and product sequencing in labour-intensive assembly cells – a case study of a bicycle assembly company

This research deals with an operator assignment problem in which cell loading and product sequencing are taken into account in labour-intensive assembly cells. In each cell the number of assembly tasks is more than the number of operators, so multi-assembly tasks are assigned to each operator. Because the assembly procedure and time required for each assembly task are quite different for different products, some tasks will be transferred when the product changes. Reducing the number of task transfers can smooth the process of product change. A four-phase methodology is proposed to minimise the total manpower required and task transfers at the same time. The four phases are manpower configuration design, calculating the number of task transfers, manpower requirement minimization and cell loading and product sequencing optimization. A case study from a bicycle assembly company is introduced. For comparison, two methodologies are applied. The results show that the proposed four phase methodology can provided the solution with fewer task transfers based on the same total manpower requirement. However, when the number of products increases, the computation time of the proposed four-phase methodology increases rapidly.     

Assembly systems layout design model for delayed products differentiation

Frequently changing customers’ needs and market pressures motivate manufacturers to offer a wide variety of their products. Poor demand prediction and increased manufacturing complexities and managerial burdens are just a few symptoms of products variety proliferation. Applying a postponement strategy is an effective method for mitigating the complexities arising due to increased products variety and customisation. Delayed product differentiation (DPD) is a prerequisite for applying form postponement strategies, where the unique features that distinguish each product are added at the final stages of production. This paper introduces an innovative design methodology to derive and represent an assembly line schematic layout for delayed products differentiation. The proposed methodology incorporates product commonality analysis and feasible assembly sequences to synthesise the assembly line layout in a single integrated logical design framework, without pre-defining either the number or the positions of differentiation points along the line. Products commonality analysis is performed using cladistics techniques commonly used for biological classification. The classical cladistics was modified to take into consideration the precedence constraints, which are required to ensure the feasibility of assembly sequences. Real product variants are used to validate the proposed DPD assembly line layout design methodology and demonstrate its merits.     

Improved approach to quality function deployment based on Pythagorean fuzzy sets and application to assembly robot design evaluation

Quality function deployment (QFD) is an effective method that helps companies analyze customer requirements (CRs). These CRs are then turned into product or service characteristics, which are translated to other attributes. With the QFD method, companies could design or improve the quality of products or services close to CRs. To increase the effectiveness of QFD, we propose an improved method based on Pythagorean fuzzy sets (PFSs). We apply an extended method to obtain the group consensus evaluation matrix. We then use a combined weight determining method to integrate former weights to objective weights derived from the evaluation matrix. To determine the exact score of each PFS in the evaluation matrix, we develop an improved score function. Lastly, we apply the proposed method to a case study on assembly robot design evaluation.     

An integrated fuzzy approach for information technology planning in collaborative product development

Collaborative product development (CPD) processes are generally based on technological infrastructures. Various information technologies (IT) are proposed every day to facilitate collaboration, integration, co-design and co-development processes. In this highly uncertain environment, a systematic methodology is essential to plan the IT infrastructure needed to start and maintain a collaborative process. This study offers an integrated IT planning methodology combining fuzzy quality function deployment, fuzzy axiomatic design and fuzzy rule-based systems. The methodology is tested in a CPD case and the outcome presents an improvement path for IT for each of the collaborative parties.     

Optimal production and pricing policies in a combined make-to-order/make-to-stock system

In this paper, we consider a production system which is capable to produce two types of products. The first type of products is make-to-order, while the second type is make-to-stock whose demand is satisfied by the on-hand inventory. The demand arrival rates of both types of products are price-sensitive. The excess demand that cannot be satisfied immediately is either backlogged or lost. The system costs include the holding costs of product inventories and shortage costs of unsatisfied demand. The objective is to maximise the total discounted profit over an infinite planning horizon by coordinating the production process and pricing decisions. By analysing the properties of objective functions, we characterise the optimal control policy by two switch curves and the optimal price is also given for different ordering and inventory levels. We also explore the monotonicity of both switch curves which will reduce the computation effort. Numerical experiments are conducted to demonstrate the use of the switch curves in managing the production system and illustrate that compared with the static pricing policy, the optimal integrated price and inventory control policy can result in a significant profit improvement in the make-to-order/make-to-stock system that is much higher than in a single-product system.     

基于广义键的产品可装配性模糊评价方法研究

提出基于广义键的产品可装配性模糊评价方法。采用多重配连接图描述产品中零件之间的多重装配关系，研究了基于模糊装配连接图中的结点和连接连的模糊度来描述和评价产品的可装配性。建立了产品可装配性评价体系；基于产品装配数据和装配知识对产品可装配性进行模糊定量评价，从而指导产品装配设计。     

Engineering design complexity: an investigation of methods and measures

In this paper, two measures are proposed for valuation of size and coupling complexities of design products as abstracted by three distinct representations. The proposed size complexity measure is based on the information theoretic definition of complexity that connects the complexity of a design to the level of entropy, or uncertainty, inherent in the design product. The proposed coupling complexity measure evaluates the decomposability of the graph-based representation of design products. To validate the proposed measures, an experiment is conducted to calculate the complexities of three consumer products based on three product representations, namely, function structure, connectivity graph, and parametric associativity graph. The findings indicate that coupling and size are independent measures of a product’s complexity. Thus, it is recommended that both measures should be used. Further, the complexity of a product is not independent of the choice of representation model used to describe the product. This suggests that the complexity of a product will vary with the selected view. Finally, it is shown that the two approaches for measuring complexity of a product are generalizable and can be applied to different representations.     

Computational method for diagnosis of variation-related assembly problems

Dimensional variations often cause expensive problems in the assembly of mechanical products especially during new product deployment. Currently, the time and labour spent on the removal of variation-related assembly problems are considerable. This paper proposes a computational method to identify the causes of variation-related problems in assemblies. In the proposed method, the relationship between causes and symptoms is computed via simulation of the assembly process, and they are represented by a matrix. For given measurement data, this method uses linear optimization and statistical techniques to diagnose assembly problems. The proposed method can diagnose assembly problems caused by either a single or multiple fault(s).     

Production rate control of an unreliable manufacturing cell with adjustable capacity

This article addresses the production control problem of an adjustable capacity unreliable manufacturing cell responding to a single product type demand. The manufacturing cell is composed of an unreliable machine, called the ‘central machine’. Due to availability fluctuations, the central machine may fall short of meeting the long-term demand rate. In order to quickly adjust the production capacity and thus meet the demand, a reserve machine is called upon in support if the finished product inventory level drops below a specific threshold. Such a machine involves higher production costs compared with the central one. This article aims to determine the optimal production control policy for the involved machines in order to minimise production, inventory and backlog costs over an infinite horizon. This article proposes a continuous dynamic programming formulation of the problem and adopted a numerical scheme to solve the optimality conditions equations. The optimal production policy is shown to be described by a state dependent hedging point policy (SDHPP). To determine the optimal control policy parameters, an experimental approach based on design of experiments, simulation modelling, and response surface methodology is proposed. Several sensitivity analyses have been carried out and have shown the robust behaviour of the developed policy facing expected variations of the system parameters. The results also show that the proposed SDHPP policy outperforms classical stand-by and parallel machines based control policies. The usefulness of the proposed approach is outlined for more complex situations where the system must deal with non-exponential failure and repair time distributions.     

Application of fuzzy quality function deployment for sustainable design of consumer electronics products: a case study

With a steep increase in the demand for consumer electronics products, the contemporary manufacturers are committed toward sustainable development of such products. There exists a scope for developing a methodology for enabling sustainable development of consumer electronics products. In this context, fuzzy quality function deployment (QFD) approach has been presented in this article in order to prioritize relevant customer requirements, sustainability parameters and sustainability initiatives. Key influential parameters for sustainable development of consumer electronics products have been identified from the literature. In the first phase of fuzzy QFD, parameters influencing sustainable development have been prioritized in accordance with customer requirements. In the second phase, environmental design initiatives have been prioritized based on critical sustainability parameters. From phase I of fuzzy QFD, ‘reduction in environmental release’ has been found as the most significant sustainability parameter with a crisp value of 22.83, and from phase II, environmental impact assessment is proved to be the significant design method with a crisp value of 20.40. The methodology would provide a comprehensive understanding to practitioners on the interrelationships among customer requirements, sustainability parameters and environmentally benign initiatives for development of consumer electronic products. The generic model developed can be applied to most of the consumer electronics product     

Development of a metric to assess the complexity of assembly/disassembly tasks in open architecture products

This paper describes two metrics to measure the complexity involved in assembly and disassembly tasks for open architecture products during its use phase. The approach proposed is based on the summary of all tasks required to assemble and disassemble a predefined set of modules to generate several product variants, which comprise different working levels or functionalities. The aim of the method is to provide a useful tool to designers in the analysis of product complexity regarding use and further phases in which the assembly and disassembly of modules are required. The benefits and usefulness of the metrics are oriented to enhance the sustainability performance of products through the measurement of complexity in modular systems for the decision-making during the design stage. The reduction of complexity involves significant benefits in all lifecycle phases of product, especially when the user or customer is responsible for many related tasks (maintenance, upgrading, reconfiguration and final disposal of modules). The metrics and their calculation process are illustrated using two case study products.     

Development and evaluation of cross-training policies for manufacturing teams

This study addresses the problem of developing and evaluating cross-training policies for manufacturing teams from a Human Resource Management (HRM) and Operations Management (OM) viewpoint. A cross-training policy can be regarded as a set of rules to determine the distribution of workers' skills. The specific way in which workers and machines are connected determines the agility of the workforce. In this article, we develop an integer goal programming model to support a consequent application of alternative cross-training policies. A simulation study is performed to assess the performance of the resulting cross-training configurations within three routing structures: a parallel structure, a serial structure, and a job shop structure. Results indicate that within all routing structures, the focus of cross-training policies depends on whether a HRM or an OM viewpoint is considered. Within the parallel and the serial structures, however, HRM and OM goals are compatible and can be integrated within a single cross-training policy. Within the job shop structure, the integration of both OM and HRM goals within one cross-training policy is more difficult.     

A methodology of integrating affective design with defining engineering specifications for product design

Affective design and the determination of engineering specifications are commonly conducted separately in early product design stage. Generally, designers and engineers are required to determine the settings of design attributes (for affective design) and engineering requirements (for engineering design), respectively, for new products. Some design attributes and some engineering requirements could be common. However, the settings of the design attributes and engineering requirements could be different because of the separation of the two processes. In previous studies, a methodology that considers the determination of the settings of the design attributes and engineering requirements simultaneously was not found. To bridge this gap, a methodology for considering affective design and the determination of engineering specifications of a new product simultaneously is proposed. The proposed methodology mainly involves generation of customer satisfaction models, formulation of a multi-objective optimisation model and its solving using a chaos-based NSGA-II. To illustrate and validate the proposed methodology, a case study of mobile phone design was conducted. A validation test was conducted and the test results showed that the customer satisfaction values obtained based on the proposed methodology were higher than those obtained based on the combined standalone quality function deployment and standalone affective design approach.