Capabilities Of Manufacturing System Research Articles

Resilience optimization in manufacturing systems using Quantum Annealing

Resilience describes the capability of manufacturing systems to resist disturbances while minimizing the loss of revenue or productivity. In order to achieve robustness against disturbances under consideration of operational costs, multiple planning parameters and strategies must be taken into account simultaneously. This leads combinatorial optimization problems with complex modeling and time-consuming computations. To still evaluate many strategies within a short time Quantum Annealing (QA) can be used, which shows potentials to solve such complex assignment problems within seconds. Consequently, a QA-based resilience optimization approach for manufacturing systems is presented. The approach shows potentials regarding scalability, solution quality, and computing time.

Modelling and optimization of distributed heterogeneous hybrid flow shop lot-streaming scheduling problem

More enterprises are facing rapid and changing market demand and small but frequent orders, and they extend the production capability of manufacturing systems to respond to these changes. This paper studies a distributed heterogeneous hybrid flow shop lot-streaming scheduling problem (DHHFLSP) with the minimization of makespan. In the DHHFLSP, the processing capacity of each factory is different and each job can be split into several sub-lots. These sub-lots are assigned to several non-identical factories. The mixed-integer linear programming model (MILP) of DHHFLSP is established. To solve the DHHFLSP, eighteen constructive heuristics and an iterated local search algorithm (ILS) are designed. In constructive heuristics, the jobs are sorted according to several time-based heuristic rules or they are divided into several groups according to bottleneck stages, and then these jobs are assigned into factories through two NEH-based job assignment rules. In the ILS, the NEH-based heuristic (NEHafter) plus Largest medium rule is used to generate an initial solution. Two greedy insertion operators with or without critical factories are adopted to generate the perturbation solutions. Four greedy local search operators are designed to make a deep search. The influence of the parameters and main components are investigated by a comprehensive analysis. The comparisons with several related algorithms on extensive testing instances demonstrate the effectiveness and efficiency of the ILS algorithm.

Design for Agile Manufacturing: Product Design Principles that Enhance Agile Manufacturing of Powertrain Systems

While companies in the entire automotive industry deal with increasing volatility and uncertainty, new trends and innovations pressure especially powertrain margins. The concept of agile manufacturing enables companies to remain competitive in such an environment. As some authors declare that the success of agile manufacturing is largely determined by the design of products, this paper investigates how these two phases in the powertrain lifecycle can be linked. A literature review was conducted to identify DFX guidelines that reflect the agile manufacturing characteristics: flexibility, profitability, speed, proactivity and quality. More than 200 design principles were collected and clustered into seven design objectives according to their main purposes. A first questionnaire was conducted at an engineering company having its main business field in powertrain development in order to define the importance of these principles to enhance agile powertrain manufacturing. The results are presented in a design catalogue. Through an additional literature review the required capabilities of manufacturing systems to fulfill the five agile characteristics were identified. The rating of these capabilities was subject of a second questionnaire at several manufacturing companies in the automotive industry. The employment of a domain mapping matrix supports the selection and application of appropriate product design principles aiming to enhance specific agile manufacturing capabilities. Finally, the developed procedure model was evaluated.

Expanding Industrial Architecture Through Creativity in Manufacturing

Throughout the decades, industrial firms have sought clearly in calling on industry production experts to production more producible prototypes for manufacturing purposes. This can typically be accomplished by evaluating the current product production manufacturing system capabilities, and difficulties often arise due to challenges to combining product description and manufacturing operations. This paper will discuss how advances in manufacturing (as new fabrication capabilities) will add to the industrial design space for product design engineers, enabling more design flexibility and increasing efficiency by eliminating and/or loosening constraints on product designs. The findings from a series of industrial case studies provide encouraging effects on how technological technologies will positively impact the growth of industrial design engineers' solution space. The findings from a series of industrial case studies provide encouraging effects on how technological technologies will positively impact the growth of industrial design engineers' solution space. To order to foster product creativity, design managers are expected to test new technologies, new design techniques and new manufacturing (working) practices. Keywords: Industrial Design; Design for X; Design to X, Product Innovation, Manufacturing Systems, Production Innovation. DOI: 10.7176/JRDM/71-05 Publication date: November 30 th 2020

Association rule mining using chaotic gravitational search algorithm for discovering relations between manufacturing system capabilities and product features

An effective data mining method to automatically extract association rules between manufacturing capabilities and product features from the available historical data is essential for efficient and cost-effective product development and production. This article proposes a chaotic gravitational search algorithm–based association rule mining method for discovering the hidden relationship between manufacturing system capabilities and product features. The extracted rules would be utilized to predict capability requirements of various machines for the new product with different features. We use two strategies to incorporate chaos into gravitational search algorithm: one strategy is to embed chaotic map functions into the gravitational constant of gravitational search algorithm; the other is to use sequences generated by chaotic maps to substitute random numbers for different parameters of gravitational search algorithm. In order to improve the applicability of chaotic gravitational search algorithm–based association rule mining, a novel overlapping measure indication is further proposed to eliminate those unuseful rules. The proposed method is relatively simple and easy to implement. The rules generated by chaotic gravitational search algorithm–based association rule mining are accurate, interesting, and comprehensible to the user. The performance comparison indicates that chaotic gravitational search algorithm–based association rule mining outperforms other regular methods (e.g. Apriori) for association rule mining. The experimental results illustrate that chaotic gravitational search algorithm–based association rule mining is capable of discovering important association rules between manufacturing system capabilities and product features. This will help support planners and engineers for the new product design and manufacturing.

Engineering Design Featuring the Life Cycle Approach for Reconfigurable Machine Tool

The evolution of design has come of age and the new design approaches that look at the rapid change and short life cycles of products is taking the centre stage. Competitiveness and the cost of products determine the lifeline of an organisation. The traditional machine tools such as the dedicated and flexible machines are designed on the principle of machine design. The development of reconfigurable machines seeks a new approach to design that not only encompasses the existing approaches but should include new design approaches as well. The success of a designed product maybe measured by the capability of the system that produces it. It is critical when designing a product that the organisation’s technological and manufacturing system capabilities be considered as failure to do so may lead to production designs that are not manufacturable. A good design system ensures quick delivery of a quality, reliable and safe product. This research therefore seeks to develop an integrated approach to design that incorporates design for manufacturing, design for assembly, concurrent engineering, eco-design and reconfigurable design as critical components for reconfigurable machine tool. Literature on these systems was reviewed to integrate the different design paradigms. The results of the study give a new approach to a reconfigurable machine design based on the integration of the five design approaches and their impact in the life cycle of a product.

Conducting Clinical Risk Assessments for Visible Particulate Matter in Parenteral Preparations.

Visible particulate matter in injectables presents one important question for consideration: "What are the potential implications to the patient?" The risks of visible particulate matter to patient safety have been comprehensively reviewed elsewhere. However, the methods used to assess and characterize the risks have been explained with various degrees of specificity and supporting rationale. To date, the assessment process lacks the necessary consensus to permit a more standardized and consistent approach to evaluate the potential patient risks.The purpose of this commentary is to provide one model that might be used to evaluate the three most relevant factors impacting the risk of injections containing particulate matter: the source of the particle, particle-specific attributes, and characteristics of the intended patient population. Each of these factors is considered with a focus on the more important aspects that might be relevant to imposing untoward risk. The discussion also includes the importance of differentiating the concepts of risk assessment from risk acceptance when establishing criticality levels for product attributes.LAY ABSTRACT: Pharmaceutical products intended for injection or infusion may contain particles that can emanate from different sources. Some particles, such as suspensions, are intended. Others are not, and those particles are the subject of rigorous manufacturing process controls to limit their presence and reject units that might contain visible defects. However, no technology exists that can prevent or eliminate all particles from these products. As a result, comprehensive risk assessments must be conducted to identify the capability of manufacturing systems to limit particles and detect and reject atypical units. An essential component of this strategy includes understanding the potential impact that injected or infused particles might have to a patient receiving these medications. The purpose of this paper is to provide one approach that clinicians might use to conduct that risk assessment by discussing the important aspects of the source of the particle, its characteristics (such as size or composition), and the relevant patient factors such as the illness being treated or other medical conditions that might impact the risk to these patients if particles are injected or infused.

Assessment of corporate innovation capability with a data-mining approach: industrial case studies

The interest in assessment of innovation capability of manufacturing systems is fueled by the growing competition. At this time, there is no generally accepted model to evaluate innovation capability of manufacturing systems. In this paper, a fuzzy-logic based data-mining approach is proposed to assess innovation capability of manufacturing systems. The proposed algorithm is illustrated with two industrial case studies representing two different industry sectors. The results derived from these case studies demonstrate advantages of the proposed algorithm in assessing corporate innovation capability.

An integer programming model for discovering associations between manufacturing system capabilities and product features

Valuable implicit knowledge and patterns are accumulated over time in industrial databases at various stages of product development and production. An example of such hidden patterns would be the cutting tool which is typically used to produce a profiling feature in a given steel part. Discovering and interpreting such patterns would be useful in supporting and optimizing the operations and planning activities such as process planning and manufacturing systems synthesis. A novel knowledge discovery model is introduced to extract useful correlations between the manufacturing domain and design domain based on historical manufacturing data. An Integer Programming model is developed, for the first time, to extract association rules between sets of various product features and manufacturing capabilities used in their production. These associations identify the specific manufacturing system capabilities associated with (i.e. typically used for) the production of each product feature. The discovered knowledge is then used to synthesize the required manufacturing system capabilities for new products with new combinations of features. The proposed IP model was demonstrated using a case study of seven instances of machined parts and the corresponding milling machines used to produce them. The advantages of the proposed association rule discovery IP model were also demonstrated by comparing it with existing association rule discovery methods. The proposed model is simple and easy to implement and automate. Utilizing the proposed model in manufacturing system synthesis should greatly assist in speeding-up product development and manufacturing systems design and re-design.

Impact of human factors and errors for product quality and reliability in the integrated approach of product and process design, maintenance and production

Globalization is the main challenge for all organi-zations developing and producing technical products today. This paper deals with develop an integrated approach to achieve the least manufacturing cost and delivery time to the customer applying concurrent development of product and process keeping the onward end of the maintenance and production process. In this paper, the belief and plausibility computations and forecasting according to the evidence theory for classifying product and its parts failures are also carried out to highlight the capabilities of manufacturing system aiming the highest production quality and reliability. The theoretical consumptions of this research have been checked and confirmed in case study – Large Lithuanian Company Y that develops and produces bicycles and their components. At the further work it is planned to create for each product and process failure case, the case needs to be classified in terms of causes and entered in the knowledge base (KB). DOI: http://dx.doi.org/10.5755/j01.mech.20.1.5258

A mechanism for external competence transfer to improve manufacturing system capabilities and market performance

This study uses competence transfer theory to establish a mechanism for transferring competences into an organization from the outside. It develops a research framework that describes the impact of communication on a firm's knowledge base and as well as its ability to bring external competence into the firm. Data were collected in the US from 288 manufacturing companies. The mechanism of competence transfer is empirically supported. As the level of transferred competences increase, a firm's manufacturing process competences including process automation, process integration, and process modularity increase. Furthermore, process competences lead to higher market performance.

Developing a reconfigurability index using multi-attribute utility theory

Reconfigurable manufacturing systems (RMSs) have been acknowledged as a promising means of providing manufacturing companies with the required production capacities and capabilities. This is accomplished through reconfiguring the system elements over the time for a diverse set of individualised products often required in small quantities and with short delivery lead time. This necessitates the requirement of mapping the manufacturing system capabilities and other characteristics by developing a suitable index. In this paper an index has been developed to measure the reconfigurability of RMSs keeping in mind their various core characteristics such as modularity, scalability, convertibility and diagnosability. These characteristics have been mapped together using multi-attribute utility theory. One could easily use this index to find the reconfigurability of a system possessing different characteristics. An illustrative example is provided to reveal the application of the proposed methodology on a given system. Insight gained would be of much interest to the decision makers managing the complexity of a manufacturing system for diversified products.

Structural modelling and integrative analysis of manufacturing systems using graph theoretic approach

PurposeThe purpose of this paper is to attempt to integrate manufacturing system analysis to obtain system‐wide optimized solutions and to increase the level of comprehensiveness of the manufacturing system modelling and to develop method of characterization of manufacturing systems based on its structure.Design/methodology/approachElements constituting the manufacturing plant and the interactions between them have been identified through a literature survey and have been represented by graph‐based model. The matrix models and the variable permanent function models are developed for carrying out decomposition, characterization and the total analysis.FindingsStructural patterns and combination sets of subsystems interacting in various ways have been recognized as capabilities of manufacturing system in different performance dimensions. The permanent function of the manufacturing system matrix has been proposed as a systematic technique for structural analysis of manufacturing system. Also, the terms of permanent multinomial characterize the manufacturing systems uniquely and are highly useful for computational storage, retrieval, communication as well as analysis of the structural information of manufacturing system.Research limitations/implicationsThe structure‐based characterization technique developed has the potential of aiding the ongoing research activities in the field of benchmarking, and business process reengineering. The graph theory‐based methodology will serve as a framework to develop composite performance measures building on the performance measures of the individual elements of the manufacturing system graph in various dimensions.Practical implicationsThrough the use of proposed methodology, a manufacturing manager will be able to make better informed decisions towards organizational efforts of improving the productivity and speed. For aiding several decisions, different “what‐if” scenarios may be generated with several structural modifications.Originality/valueThis graph theory‐based methodology is a novel mechanism to seamlessly integrate manufacturing system giving way to system wide optimization. The paper is an attempt to address the need for comprehensive and integrated analysis of the manufacturing system.

A technique for advanced manufacturing systems capability evaluation and comparison (ACEC)

This paper proposes a generic technique for the evaluation and comparison of the capability of manufacturing systems as a decision-making aid. It provides a methodical approach for extracting key capability factors (CF) and their degree of fulfilment by the institutes. The capability factors and their priorities are determined by experts in the related industry. By adopting this approach, a “capability index” for each institute will be derived. This will be the basis for capability comparison. The proposed method applies fuzzy relations and analytic hierarchy process (AHP) techniques to calculate capability indices. The case study discussed in this paper is the result of a project commissioned by a prominent UK based company (UBC) to consolidate its EU operations. The results illustrate the effectiveness and flexibility of the proposed methodology for a wide range of applications.

Product Design and Manufacturing Process Improvement Using Association Rules

Modern manufacturing systems equipped with computerized data logging systems collect large volumes of data in real time. The data may contain valuable information for operation and control strategies as well as providing knowledge of normal and abnormal operational patterns. Knowledge discovery in databases can be applied to these data to unearth hidden, unknown, representable, and ultimately useful knowledge. Data mining offers tools for discovery of patterns, associations, changes, anomalies, rules, and statistically significant structures and events in data. Extraction of previously unknown, meaningful information from manufacturing databases provides knowledge that may benefit many application areas within the enterprise, for example improving design or fine tuning production processes. This paper examines the application of association rules to manufacturing databases to extract useful information about a manufacturing system's capabilities and its constraints. The quality of each identified rule is tested and, from numerous rules, only those that are statistically very strong and contain substantial design information are selected. The final set of extracted rules contains very interesting information relating to the geometry of the product and also indicates where limitations exist for improvement of the manufacturing processes involved in the production of complex geometric shapes.

Markovian Models for Investigating Failure and Repair Characteristics of Production Systems

Abstract This paper presents a Markov chain approach for investigating the steady-state production capability of manufacturing systems in terms of specified reliability and maintainability characteristics. Three general classes of models are developed. The first model considers a system with only elements which cause the system to immediately shut down when the first failure happens; the second model considers a system with only elements which cannot be repaired while other elements are functioning; the third model considers a system with only elements which can be repaired while other elements are in operation.

Constraint calculus for the optimal selection of manufacturing systems

Abstract In this paper, a method for the binary labelling of the elemental domains of capability of manufacturing systems is described and an associated calculus for the determination of the constraints which relate to the optimal selection of manufacturing systems is presented.