Real-time performance evaluation and improvement of assembly systems with Bernoulli machines and finite production runs

Extensive research has been investigated in the past several decades to evaluate the performance of manufacturing systems under rigid production mode. Based on the deployment of the new manufacturing strategies (e.g. smart manufacturing), real-time performance analysis, continuous improvement and efficient production management of flexible production systems are urgently to be investigated. Therefore, we study the problems of real-time performance evaluation and bottleneck of assembly systems in this paper. The system is assumed to have Bernoulli machines and finite production runs. We first derive the mathematical model of the system and then, derive the analytical formulas for performance evaluation of systems with three Bernoulli machines. In addition, we propose a decomposition and aggregation-based algorithm to approximate the system performances with high accuracy and computational efficiency. The idea is then extended to generalised assembly systems. Finally, the method of bottleneck analysis by using completion time bottleneck indicator is introduced and evaluated by numerical justification.     

Optimisation of the transmission of disruptions in assembly systems

The dynamic analysis of disruption transmission in networks of closed loops formed by machines and intermediate buffers is of vital importance in most production systems. Nevertheless, little research has been done on optimisation in this field. This study analyses the disruption time transmission in a generic assembly system, which has been modelled as a network of closed loops of machines and intermediate buffers. In addition, this modelling has been used to analyse a real automobile assembly line, taking into account variables that have not previously been considered in the literature, such as working regimes of machines, their cycle times, capacities of the intermediate buffers and their minimum contents. The optimal configuration of the intermediate buffers is analysed. Dynamic outlines of these kinds of assembly systems are proposed in order to maximise the transmission of disruption times and, hence, their availability. For this purpose, an algorithm for analysing and optimising availability in this kind of manufacturing system has also been developed.     

Reforming a conventional vehicle assembly plant for job enrichment

Although conventional conveyor-based vehicle assembly systems have proved to be very efficient in terms of plant productivity, it has also been recognized as a system which puts too much pressure on people. This paper introduces an alternative to conventional conveyor-based assembly lines, one that is designed to enrich the work environment of employees without sacrificing productivity. The reforming methodology suggested here applies the idea of cell manufacturing to the conventional conveyor-based assembly line system, but it does not require making any major changes to the existing hardware configurations of the plant. Benefits of the reformed line for workers include a longer cycle time, more balanced work loads, and greater protection against developing musculoskeletal disorders. To prove the effectiveness of the suggested methodology, we built a virtual factory model and performed simulations to assess the performance of the reformed line.     

Smart production systems: automating decision-making in manufacturing environment

Smart production systems (SPS) are manufacturing systems capable of autonomously diagnosing their health and autonomously designing continuous improvement projects, leading to the desired productivity improvement. The main component of SPS, developed in this paper, is the Programmable Manufacturing Advisor (PMA), which evaluates the system's health and calculates optimal steps for continuous improvement. The analytics of PMA are based on the theory of Production Systems Engineering (PSE); the numerics of PMA are based on PSE Toolbox, which implements the PSE methods. In this paper, the PMA-based SPS architecture with manager-in-the-loop is described, theoretical/analytical foundations of PMA are outlined, its software/hardware implementations are commented upon, and demonstrations of PMA-based SPS operation are provided using two production systems: automotive underbody assembly (large volume manufacturing) and hot-dip galvanisation plant (small manufacturing organisation).     

Computational modelling of manufacturing choice complexity in a mixed-model assembly line

Manufacturing systems have evolved to adopt a mixed-model assembly line enabling the production of high product variety. Although the mixed-model assembly system with semi-automation (i.e. human involvement) can offer a wide range of advantages, the system becomes very complex as variety increases. Further, while the complexity from different options can worsen the system performance, there is a lack of quantifiable models for manufacturing complexity in the literature. Thus, in this paper, we propose a novel method to quantify manufacturing choice complexity for the effective management of semi-automated systems in a mixed-model assembly line. Based on the concept of information entropy, our model considers both the options mix and the similarities between options. The proposed model, along with an illustrative case study, not only serves as a tool to quantitatively assess the impact of choice complexity on total system performance, but also provides an insight into how complexity can be mitigated without affecting the overall manufacturing throughput.     

Change management in modular assembly systems to correspond to product geometry change

Modular assembly systems are a category of changeable manufacturing systems, which can handle the rapid change in customer demands, product design change and market fluctuations. On the operational level, jigs and fixtures are fundamental elements of assembly systems. They are used to hold parts and subassemblies in place, and directly affect assembly cost, quality and time. Therefore, modular fixtures that can adapt to different geometries are becoming a very important enabler for changeable manufacturing. In this paper, two mathematical models are presented to optimise the use of a passive modular assembly fixture plan in an automated assembly system by considering different production scenarios and constraints. These models optimise the changeability plan of the modular fixture by minimising the number of dowel replacements between different part geometries assuming that the candidate dowels locations for each part have been determined using existing methods in the literature by considering different assembly requirements. The first model, LRTE, considers all possible part rotations and translations on the fixture to minimise setup time. In addition, the second model, SLRTE, enables the system to simultaneously optimise job sequence. This paper presents various examples in different sizes, and the results show that the model can effectively reduce the fixture setup time up to %50.     

An improved time line search algorithm for manufacturing decision-making

The coloured Petri net formalism has been recently used to analyse and optimise manufacturing systems making use of the state space (SS) analysis. This approach has great potential for scheduling and production planning purposes when it is properly implemented. In this article, an improved version of the algorithm known as the time line search for optimising the makespan of manufacturing models is presented. The algorithm has been developed for the use in a compact SS of coloured Petri net models in order to analyse the highest possible number of manufacturing configurations for the improvement of the makespan of a production system. The proposed algorithm can be used for the developing of decision support tools in manufacturing or operational decision-making.     

A multi-decision genetic approach for workload balancing of mixed-model U-shaped assembly line systems

A mixed-model assembly line is a type of production line where a variety of product models similar in product characteristics are produced. As a consequence of introducing the just-in-time (JIT) production principle, it has been recognised that a U-shaped assembly line system offers several benefits over the traditional straight line system. This paper proposes a new evolutionary approach to deal with workload balancing problems in mixed-model U-shaped lines. The proposed method is based on the multi-decision of an amelioration structure to improve a variation of the workload. This paper considers both the traditional straight line system and the U-shaped assembly line, and is thus an unbiased examination of line efficiency. The performance criteria considered are the number of workstations (the line efficiency) and the variation of workload, simultaneously. The results of experiments enhanced the decision process during multi-model assembly line system production; thus, it is therefore suitable for the augmentation of line efficiency in workstation integration and simultaneously enhancement of the variation of the workload. A case study is examined as a validity check in collaboration with a manufacturing company.     

Order-oriented cooperative sequencing optimisation in multi-mix-model assembly lines

Order-oriented products assembly sequence among different assembly lines becomes a critical problem for mass customisation manufacturing systems. It significantly affects system productivity, delivery time, and manufacturing cost. In this paper, we propose a new approach to extend the traditional products sequencing from mixed model assembly line (MMAL) to multi-mixed model assembly lines (MMMALs) to obtain the optimal assembly sequence with the objectives of minimising consumption waviness of each material in the lines, assembly line setup cost, and lead-time. A multi-objective optimisation algorithm based on variable neighbourhood search methods (VNS) is developed. We perform an industrial case study in order to demonstrate the practicality and effectiveness of the proposed approach.     

Simulation optimisation of pull control policies for serial manufacturing lines and assembly manufacturing systems using genetic algorithms

Several efficient pull production control policies for serial lines implementing the lean/JIT manufacturing philosophy can be found in the production management literature. A recent development that is less well-studied than the serial line case is the application of pull-type policies to assembly systems where manufacturing operations take place both sequentially and in parallel. Systems of this type contain assembly stations where two or more parts from lower hierarchical manufacturing stations merge in order to produce a single part of the subsequent stage. In this paper we extend the application of the Base Stock, Kanban, CONWIP, CONWIP/Kanban Hybrid and Extended Kanban production control policies to assembly systems that produce final products of a single type. Discrete-event simulation is utilised in order to evaluate the performance of serial lines and assembly systems. It is essential to determine the best control parameters for each policy when operating in the same environment. The approach that we propose and probe for the problem of control parameter selection is that of a genetic algorithm with resampling, a technique used for the optimisation of stochastic objective functions. Finally, we report our findings from numerical experiments conducted for two serial line simulation scenarios and two assembly system simulation scenarios.     

ISTS: A new procedure for the integrated scheduling of multi-stage systems

This paper addresses the problem of scheduling a two-stage manufacturing system. MRP systems have been developed to synchronize production in multistage systems, assigning due dates to production at each stage. However, MRP systems allow just a broad scheduling and it is therefore up to the short term scheduling system to meet such due dates. Previous research work, and industrial practice, have developed independent scheduling systems for each stage, relying on MRP to synchronize them. Resulting performances are not satisfactory because, quite often, many components are late, and assembly schedules are disrupted. Recent research works on assembly shops have shown that improvements in performances can be achieved if assembly constraints and dependencies between jobs are also considered at the short term scheduling level. Based on the idea that these findings can be valid for multi-stage manufacturing systems, this research work presents a new short term scheduling procedure which, on the one hand adopts two different scheduling systems for the machining stage and the assembly stage, and on the other, highly integrates short term scheduling of different stages. The former exploits the different characteristics of the two subsystems. In particular, unlike all previous research work, assembly constraints and dependencies between jobs are taken into consideration at the machining stage, both at the dispatching level, and at the Order Review and Release level.     

Modeling and Analysis of Assembly Systems with Unreliable Machines and Finite Buffers

An assembly line is a tree-structured manufacturing system in which some machines perform assembly operations. In this paper, we consider assembly lines with the following features: every operation is performed in a fixed amount of time, machines are unreliable, and buffers have finite capacity. Usually, the times to failures of machines are much larger than the processing times. This allows us to approximate the behavior of these systems by a continuous flow model. The behavior of this model is then analyzed using a decomposition technique which is an extension of an earlier technique proposed in the case of transfer lines. An efficient algorithm for calculating performance measures such as production rate and average buffer levels is derived. Experimental results are provided showing mat this approximate method is quite accurate.     

Risk-based analysis of manufacturing systems

A manufacturing system considered here consists of a machine that processes parts and an automatic conveyor that transports immediately a finished part to an assembly cell (i.e. a single workstation facility is examined). The system can hold a maximum number of processed parts on the conveyor, which determines its size. Modelling the system as a family of Birth–Death Processes with finite size in equilibrium, indexed by the system utilisation parameter, and depending on the concepts of system information and system entropy (i.e. mean information), we promote a risk-based analysis of manufacturing systems. The current number of processed parts on the conveyor determines the system particular states. The performance measures of a system are: risk (i.e. uncertainty) of the system (represented by system entropy), throughput of the system, utilisation of the machine, utilisation of the conveyor, and information range of the system. They are simultaneously investigated with respect to the system utilisation parameter, in order for an optimal trade-off among them to be established. This analysis is illustrated on the information linear, Erlang, Binomial and Pascal held manufacturing systems. Regarding the managerial insights, a use case of a system target output is considered, comparing the above system types. This approach can also be used for analysis of an assembly line consisting of multiple machines that have different operation times and buffers between them.     

Framework for designing a flexible cellular assembly system

Modern manufacturing companies have to face competition in a turbulent world market that requires them to improve their operating performances according to increasingly differentiated products with shorter life cycles, low volumes and reduced customer delivery times. The aim of the present paper is to develop a conceptual framework for the simultaneous design and control of a flexible, agile reconfigurable and robust assembly system in conjunction with the analysis and optimization of product, process, system structure, material-handling devices and plant layout. An effective solution for reconfigurability and agility in assembly to order and batch-type systems is a modular semi-automatic approach based on cellular flexible facilities: modularity, automation and human skills are combined to gain the advantages of mass production. Families of parts are produced in flexible cells, i.e. groups of various machines and resources that are physically close together and process one or more families of similar parts. The proposed approach is based on a multistage iterative procedure that integrates different supporting decision techniques and tools such as design for assembly, group technologies and cellular manufacturing. An application to the optimization of a semi-automatic flexible assembly system is illustrated: the system performances of example alternative solutions are presented and compared.     

Throughput analysis of production systems: recent advances and future topics

Throughput analysis is important for the design, operation and management of production systems. A substantial amount of research has been devoted to developing analytical methods to estimate the throughput of production systems with unreliable machines and finite buffers. In this paper we summarise the recent studies in this area. In addition to the performance evaluation of serial lines, approximation methods for more complex systems, such as assembly/disassembly systems, parallel lines, split and merge, closed-loop systems, etc., are discussed. Moreover, we propose future research topics from the automotive manufacturing systems perspective.     

Systemic criterion of sustainability in agile manufacturing

Agile manufacturing systems work in a constantly changing global market, particularly assembly systems at the last stage of product differentiation. Meanwhile, sustainability is becoming a key issue for manufacturing strategy. This paper formulates a systemic criterion of sustainability in agile manufacturing and computes it through flexibility and complexity. It is defined as a ratio of utility and entropy as a sustainability measurement. Under a unified framework, utility allows one to quantify the contributions to agility, in particular system flexibility. Complexity is measured by entropy. Thus, an original complementary role of flexibility and the complexity of the system are proposed. Developed from the distribution of system states, the systemic approach to sustainability in terms of output evolution is enriched. Based on a simple assembly line integer model simulation, a first quantitative analysis illustrates the concepts introduced.     

基于XGBoost的车身尺寸装配质量智能预测模型

针对汽车多级制造系统中传统机器学习方法处理多元数据样本时间久、精度低等问题,提出一种基于XGboost的车身尺寸装配质量智能预测模型,解决多级制造系统的车身装配精准预测控制问题。首先,通过对车身多级装配过程的分析,对数据样本进行预处理,建立基于Spearman系数的不同特征要素的绝对相关性矩阵;其次,对生产流程的相关数据实时采集、清洗及挖掘分析,提出数据分析流程与数据处理框架,建立基于XGBoost的车身尺寸装配质量智能预测模型,并通过对模型性能的有效评估实现对车身尺寸装配的精准控制;最后,仿真实例对比分析表明,基于XGboost的质量智能预测模型能精准地解决多级制造系统中的车身装配质量控制问题。     

A genetic algorithm for the stochastic mixed-model U-line balancing and sequencing problem

Mixed-model assembly lines are widely used to improve the flexibility to adapt to the changes in market demand, and U-lines have become popular in recent years as an important component of just-in-time production systems. As a consequence of adaptation of just-in-time production principles into the manufacturing environment, mixed-model production is performed on U-lines. This type of a production line is called a mixed-model U-line. In mixed-model U-lines, there are two interrelated problems called line balancing and model sequencing. In real life applications, especially in manual assembly lines, the tasks may have varying execution times defined as a probability distribution. In this paper, the mixed-model U-line balancing and sequencing problem with stochastic task times is considered. For this purpose, a genetic algorithm is developed to solve the problem. To assess the effectiveness of the proposed algorithm, a computational study is conducted for both deterministic and stochastic versions of the problem.     

Investigations into the impact of flexibility on manufacturing performance

This paper provides investigative insights into the impact of routeing flexibility, machine flexibility, and product-mix flexibility on the performance of a manufacturing plant. The study employs simulation modelling as the primary tool. The facility modelled is an automobile engine assembly plant consisting of a FMS (flexible manufacturing systems), job shop, and assembly line. A variety of experiments, with the FMS exhibiting one or more of the above three flexibilities at different levels, were simulated on the model. In each experiment the manufacturing performance as given by flow time and work-in-process inventory was tracked. The experiments focused first on the FMS itself, and then on the entire plant. Measures for the three flexibilities are introduced. The simulation results are analysed in detail. The results indicate significant performance benefits in context of the FMS, but little in context of the overall plant     

Design for manufacturing and assembly/disassembly: joint design of products and production systems

Design for Manufacturing, Assembly, and Disassembly is important in today’s production systems because if this aspect is not considered, it could lead to inefficient operations and excessive material usage, both of which have a significant impact on manufacturing cost and time. Attention to this topic is important in achieving the target standards of Industry 4.0 which is inclusive of material utilisation, manufacturing operations, machine utilisation, features selection of the products, and development of suitable interfaces with information communication technologies (ICT) and other evolving technologies. Design for manufacturing (DFM) and Design for Assembly (DFA) have been around since the 1980’s for rectifying and overcoming the difficulties and waste related to the manufacturing as well as assembly at the design stage. Furthermore, this domain includes a decision support system and knowledge base with manufacturing and design guidelines following the adoption of ICT. With this in mind, ‘Design for manufacturing and assembly/disassembly: Joint design of products and production systems’, a special issue has been conceived and its contents are elaborated in detail. In this paper, a background of the topics pertaining to DFM, DFA and related topics seen in today’s manufacturing systems are discussed. The accepted papers of this issue are categorised in multiple sections and their significant features are outlined.