Reconfiguration Effort Research Articles

A hybrid task-constrained motion planning for collaborative robots in intelligent remanufacturing

Industrial manipulators have extensively collaborated with human operators to execute tasks, e.g., disassembly of end-of-use products, in intelligent remanufacturing. A safety task execution requires real-time path planning for the manipulator’s end-effector to autonomously avoid human operators. This is even more challenging when the end-effector needs to follow a planned path while avoiding the collision between the manipulator body and human operators, which is usually computationally expensive and limits real-time application. This paper proposes an efficient hybrid motion planning algorithm that consists of A∗ algorithm and an online manipulator reconfiguration mechanism (OMRM) to tackle such challenges in task and configuration spaces, respectively. A∗ algorithm is first leveraged to plan the shortest collision-free path of the end-effector in task space. When the manipulator body is risky to the human operator, our OMRM then selects an alternative joint configuration with minimum reconfiguration effort from a database to assist the manipulator to follow the planned path and avoid the human operator simultaneously. The database of manipulator reconfiguration establishes the relationship between the task and configuration space offline using forward kinematics, and is able to provide multiple reconfiguration candidates for a desired end-effector’s position. The proposed new hybrid algorithm plans safe manipulator motion during the whole task execution. Extensive numerical and experimental studies, as well as comparison studies between the proposed one and the state-of-the-art ones, have been conducted to validate the proposed motion planning algorithm.

A methodology for part family formation in reconfigurable manufacturing systems using Shannon's entropy method

For effective utilization of resources, Operation Management plays an important role in businesses and organizations. It basically coordinates the efforts of people to fulfil the goals and objectives decided by the organization. Operation Management is a supporting system to carry out businesses. From the point of generation of raw material to the point of consumption of goods, it directs and controls the organization. It makes a path to a manufacturing system to fulfil its goal. For full utilization of resources in an uncertain environment, the manufacturing system faces various challenges in this century. The manufacturing systems must be responding rapidly to market changes. For effective management, a new paradigm in the manufacturing system is the Reconfigurable manufacturing systems, which are built around a part family to face such challenges in an uncertain environment. The authors have developed a methodology for part family formation using attributes modularity, reconfiguration effort, longest common subsequence, etc. in the present work. The developed methodology has been discussed using an example.

Towards human-centric reconfigurable manufacturing systems: Literature review of reconfigurability enablers for reduced reconfiguration effort and classification frameworks

The unpredictable market scenario in the manufacturing industry demands the adoption of reconfigurability enablers. These enablers reduce the reconfiguration effort throughout the system life cycle and allow frequent reconfigurations of the manufacturing system. Despite the relevance of the subject, examples and concepts of reconfigurability enablers are fragmented in literature. Therefore, this study systematically reviews literature in order to: (i) outline the state of the art on reconfigurability enablers in automated, mixed and manual systems; and, (ii) provides classification frameworks for reconfigurability enablers for manufacturing systems, machines, robots, material handling systems, and operators. Additionally, new reconfigurability enablers related to Industry 4.0 are outlined, which connect systems and human resources with different roles and facilitate responsive adaptation of humans to changes. Directions for future research include extending the theory on reconfigurable manufacturing with fundamentals of human-centric automation and operationalising the proposed classification framework.

Simulation-based optimization of product integrations in line-less assembly systems based on digital twins

Line-less assembly systems enable increased resilience against uncertain events such as frequent integration of new product variants, material unavailability, personnel shortages and station failures. This can be achieved through the resolution of a general takt time, redundant workstations and flexible precedence graphs. Benefits arise in particular for use cases with a high number of product variants, parallel assembly of various products, and frequent integration of new products and product variants. This work presents a service-based framework for decision-support for product integrations in line-less assembly systems to meet these challenges. Based on a standardized data model serving as a basis for the digital twin, simulation models for system configurations are created automatically to reduce manual planning effort.The approach of simulation-based optimization is used to find feasible scenarios with least reconfiguration effort. Within the simulation, stochastic influences such as station failures and reactive scheduling decisions can be considered. The developed framework is verified by implementing all modules and a specific optimization model for the automated generation of scenarios after integrating a new product into the line-less assembly system. It can be shown, that recommended actions for adding, removing, or reconfiguring workstations are generated to support a production planner.

Reconfiguration effort based optimization for design problem of Reconfigurable Manufacturing System

The design problem of reconfigurable manufacturing system (RMS), depends upon part design specifications of product and system capabilities. The RMS consists of reconfigurable machines, tools, fixtures, layouts, etc. These system components are recon-figurable which makes the production system responsive to the change. This regular reconfiguration of the system’s components also requires effort. This effort affects the overall performance of the system. With maximization of the system’s component re-configurability to be more responsive towards the change, the overall effort should also be reduced to get good performance.A new reconfiguration effort index is defined, which considers all the efforts of reconfiguration at the process level, instead of just effort of machine configuration. The newly developed reconfiguration index is used as an objective function for solving the design problem of RMS, for selection of reconfigurable machine tool RMTs to get the best process plan with minimum effort of reconfiguration. A genetic algorithm-based approach is used to solve the problem. A numerical example is presented to illustrate the applicability of the proposed approach. The work is concluded with some future work directions.

Mixed-Model Assembly Line Design with New Product Variants in Production Generations

Among all the challenges which highlight the need of reconfigurability in manufacturing systems, taking into account the introduction of a new product has been rarely considered by the researchers. Indeed, taking into account the new product variants in the future production generation of the line at the initial design stage smooths the reconfiguration process of the line. This paper studies a mixed-model assembly line reconfiguration planning problem where the line consists of several resources (workers and robots). This study aims to design a line which produces a given product family with a set of product variants, and a new product variant will be added after a certain period of time, named production generation. At each generation, the production family can change with the addition/removal of a product variant. Therefore, the line needs to be reconfigured at each generation. We propose a new Mixed-Integer Linear Programming (MILP) which aims to minimize the total reconfiguration effort, the total cost of designing and reconfiguring the line taking into account the buying, selling, re-assigning the equipment and resources in the worst scenario of possible product families which are produced in several production generation. The MILP is validated through solving a simple example, and the results are given.

A systematic approach for responsiveness assessment for product and material flow in reconfigurable manufacturing system (RMS)

A reconfigurable manufacturing system (RMS) quickly changes machine configurations to adapt to variations in demand related to volume of product and design. A decision of machine configuration change is taken after considering many factors, such as time, effort and cost. This research proposes a systematic approach for responsiveness assessment for product and material flow in reconfigurable manufacturing system (RMS) by considering product and process characteristics. The proposed system uses three important metrics, namely reconfiguration effort, reconfiguration time and non-productive reconfiguration cost. The usefulness of the developed system is demonstrated with the help of an industrial case study of three hypereutectic aluminium automotive pistons from the same part family. These pistons are made of FM-425 aluminium alloy that contains 16.5 percent of silicon. The system is suitable for comparing and selecting efficient machine configurations in a reconfigurable manufacturing system.

Sequential optimisation of reconfigurable machine cell feeders and production sequence during lean assembly

ABSTRACTThis paper presents a manufacturing model for integrating reconfigurable machine cells as feeders of components to a multi-product assembly line exhibiting a prominent lean characteristic; synchronisation with Takt time. Two mathematical formulations in the form of combinatorial optimisation problems are developed to identify the best reconfiguration for the machines by optimum selection of the modules in the cells to minimise the total error with Takt time and then the optimum sequence of assembling the products to minimise the total reconfiguration time and effort. An elitist genetic algorithm (GA) meta-heuristic is employed twice in succession to search the optimal solutions for both the minimisation problems. The best machine configuration found from the first search is utilised further to identify the optimal assembly sequence. A hypothetical data set representing the features and parameters of the model in conformance with any typical mixed-model assembly is presented for illustration of computational procedure. Synchronisation among machine cells and tardiness are considered as performance evaluation measures to validate the effectiveness of the proposed model.

Assembly System Configuration Design for Reconfigurability Under Uncertain Production Evolution

Assembly system configuration determines the topological arrangement of stations with defined logical material flow among them. The design of assembly system configuration involves (1) subassembly planning that defines subassembly tasks and between-task material flows and (2) workload balancing that determines the task-station assignments. The assembly system configuration should be flexibly changed and updated to cope with product design evolution and updating. However, the uncertainty in future product evolution poses significant challenges to the assembly system configuration design since the higher cost can be incurred if the assembly line suitable for future products is very different from that for the current products. The major challenges include (1) the estimation of reconfiguration cost, (2) unavailability of probability values for possible scenarios of product evolution, and (3) consideration of the impact of the subassembly planning on the task-station assignments. To address these challenges, this paper formulates a concurrent optimization problem to design the assembly system configuration by jointly determining the subassembly planning and task-station assignments considering uncertain product evolution. A new assembly hierarchy similarity model is proposed to estimate the reconfiguration effort by comparing the commonalities among different subassembly plans of current and potential future product designs. The assembly system configuration is chosen by maximizing both assembly hierarchy similarity and assembly system throughput under the worst-case scenario. A case study motivated by real-world scenarios demonstrates the applicability of the proposed method including scenario analysis.

Assessment of a reconfigurable manufacturing system

PurposeThe purpose of this paper is to develop the methodology which can facilitate the concept of reconfiguration in the manufacturing system.Design/methodology/approachDesign methodology includes the calculation of similarity matrix, formation of part family, and selection of part family. ALC algorithm has been used for part family formation and three criteria have been considered for the selection of part family. These criteria are reconfiguration effort, under-utilization cost, and floor space cost. AHP has been used to calculate the weights of criteria and reference ideal method has been used for the selection of alternatives.FindingsIn the manufacturing system, machines should be grouped on the basis of reconfiguration cost. When the time period is less, light machines and Group 1 machines are added and removed. In the case study, the concept of reconfiguration is useful for families (A, B, C, D). Machines can be reused by adding/removing some modules of machines. The concept of reconfiguration becomes more useful when it is implemented with lean manufacturing. Lean manufacturing techniques Jidoka and Poka-yoke are used to increase the diagnosability of the system.Practical implicationsIndustrial case study has been considered.Social implicationsMarket competition is increasing rapidly and it increases the demand and variety of products, due to which manufacturing enterprises are forced to adapt a manufacturing system which can adjust its capacity and functionality quickly at low cost. To reconfigure manufacturing system from one product/product family to another product/product family, changes can be done in hardware and/or software components in response to sudden changes in the market or in regulatory requirements.Originality/valueAn integrated approach for reconfiguration has been proposed considering the industrial application. It includes weighted Jaccard function, ALCA, AHP, RIM. The methodology for calculation of reconfiguration effort, under-utilization cost, and floor space cost has been presented for industrial case.

Automatic assembly planning based on digital product descriptions

This paper proposes a new concept in which a digital twin derived from a digital product description will automatically perform assembly planning and orchestrate the production resources in a manufacturing cell. Thus the manufacturing cell has generic services with minimal assumptions about what kind of product will be assembled, while the digital product description is designed collaboratively between the designer at an OEM and automated services at potential manufacturers. This has several advantages. Firstly, the resulting versatile manufacturing facility can handle a broad variety of products with minimal or no reconfiguration effort, so it can cost-effectively offer its services to a large number of OEMs. Secondly, a solution is presented to the problem of performing concurrent product design and assembly planning over the organizational boundary. Thirdly, the product design at the OEM is not constrained to the capabilities of specific manufacturing facilities. The concept is presented in general terms in UML and an implementation is provided in a 3D simulation environment using Automation Markup Language for digital product descriptions. Finally, two case studies are presented and applications in a real industrial context are discussed.

Scheduling of Products for Reconfiguration Effort in Reconfigurable Manufacturing System

Reconfigurable manufacturing system is a responsive manufacturing system which can easily adjust its capacity and functionality with least effort and time when demand of the product changes. Reconfigurable manufacturing system (RMS) has the exactly capacity and functionality whenever is required.In the present work a methodology has been presented for scheduling of the products on the basis of reconfiguration effort in a multi-product line. For scheduling of products, three criteria have been considered; reconfiguration effort, profit over cost and due date. Integrated approach of Shannon entropy and TOPSIS has been used for scheduling of the products.

Scheduling in reconfigurable manufacturing system for uncertainty in decision variables

Reconfigurable manufacturing system is a new type of responsive manufacturing system which can adjust its setup to adjust its capacity and functionality with least effort and time when the demand for the product changes. Reconfigurable manufacturing system (RMS) has the exact capacity and functionality whenever is required.In the present work, an integrated approach of Shannon entropy and multi-attribute range evaluation (MARE) has been used for scheduling of the products. Weights of criteria have been calculated using Shannon entropy and ranking is obtained using MARE. MARE calculates the uncertainty of decision variables into the uncertainty of ranking. For scheduling of products, three criteria have been considered; reconfiguration effort, profit over cost and due date.

Reconfigurability consideration and scheduling of products in a manufacturing industry

Reconfigurable manufacturing system is a new type of manufacturing system which can change its capacity and functionality very easily and quickly whenever required. RMS (reconfigurable manufacturing system) has capacity and functionality exactly what is required. RMS is adjustable to the fluctuating demands and it can be easily upgraded with new process technology. Reconfigurability of a manufacturing system is measured in terms of cost, effort and time. It is the ability of a manufacturing system to be reconfigured quickly with low reconfiguration effort at low cost. In the present work, reconfigurability has been considered in Continental Automotive Components Pvt. Ltd. on the basis of RMS principles. A modified reconfigurable layout has been proposed for an assembly line and scheduling of the products has been done for the criteria reconfiguration effort, profit over cost and due date. Scheduling of the products has been done using the integrated approach of Shannon entropy and RIM (Reference Ideal Method). R program has been written for scheduling. Sensitivity analysis has been conducted for the problem.

Adaptive Cloud Deployment Using Persistence Strategies and Application Awareness

Management of large service centers and clouds requires adaptation to changing conditions and workload. Optimal deployments are possible on private clouds if there is full knowledge of the applications. Previous work, CloudOpt, combines large-scale linear optimization with a detailed non-linear performance model of every application to determine such deployments. However, when conditions change the new solution is independent of the previous deployment, and often requires excessive changes. Practical adaptive management needs a controlled compromise between the effort and cost of changing the current deployment, and the value lost by not making a change. This paper enhances CloudOpt by incorporating adjustable persistence techniques to constrain the deployment changes in each update. Three such techniques are compared, and the best ones reduce the reconfiguration effort at each adaptation step by about 90 percent, with about a 5-10 percent penalty in running costs. Persistence techniques impose no reduction in the scalability of CloudOpt.

IoT Interoperability—On-Demand and Low Latency Transparent Multiprotocol Translator

In the Industrial Internet of Things (IIoT) there is a clear need for a high level of interoperability between independently developed systems, often from different vendors. Traditional methods of interoperability including protocol gateways and adapters are often used at the network layer. Recent work on application interoperability has emphasized the use of middleware or protocol proxy/gateway. However, middleware tends to move the interoperability problem rather than solving it, and there are scalability issues with increasing the number of proxies, reconfiguration effort, and required bandwidth and processing overheads. This paper proposes a secure, on-demand, and transparent protocol translator for the IIoT. Targeting the challenge of interoperability between Internet protocol-based communication protocols, this paper analyzes current solutions and develops a set of requirements to be met by IoT protocol interoperability. The proposed protocol translator is not a middleware, it is a service-oriented architecture-based participant, it is used on-demand when needed, it does not introduce design time dependencies, it operates transparently, it supports low-latency, and it is secured through the use of Arrowhead authorization and authentication.

Design of reconfigurable flow lines using MOPSO and maximum deviation theory

Reconfigurable manufacturing system (RMS) is a state-of-the-art technology, which offers the exact capacity and functionality needed, through rapid and cost-effective reconfigurations in its modular structure. The reconfigurable machine tools (RMTs) can perform a variety of operations in its existing configuration and can further be reconfigured to change the operational capabilities. Thus, the selection of a machine configuration plays a vital role not only in the cost-effectiveness but in the future reconfiguration effort requirements. In the present study, authors have attempted a multiple-objective optimization of RMS flow line configuration, taking the cost, machine utilization, operational capability, and configuration convertibility as the conflicting objectives. The cost and machine utilization represent the economic justification while the operational capability and the configuration convertibility portray the ability of rapid and cost-effective reconfiguration ability. The emphasis of this research is to design the economic RMS configuration, which can rapidly and cost-effectively respond to the volatile market conditions. Multiple-objective particle swarm optimization (MOPSO) has been implemented to handle the discrete and discontinuous search space. The large number of Pareto frontiers is further ranked to avoid subjectiveness and imprecision in the decision making, based on the composite scores obtained through maximum deviation theory. A numerical illustration is presented to illustrate the developed methodology of reconfigurable flow line configuration design.

Constrained Information Pattern reconfiguration in Fault tolerant control of distributed systems

Given a fault tolerance strategy and a distributed control system, the set of recoverable faults depends on the information pattern that is implemented. This paper considers the reconfiguration of the information pattern, while introducing constraints to minimise the reconfiguration effort.

Systematic uncertainties in long-baseline neutrino oscillations for largeθ13

We study the physics potential of future long-baseline neutrino oscillation experiments at large $\theta_{13}$, focusing especially on systematic uncertainties. We discuss superbeams, \bbeams, and neutrino factories, and for the first time compare these experiments on an equal footing with respect to systematic errors. We explicitly simulate near detectors for all experiments, we use the same implementation of systematic uncertainties for all experiments, and we fully correlate the uncertainties among detectors, oscillation channels, and beam polarizations as appropriate. As our primary performance indicator, we use the achievable precision in the measurement of the CP violating phase $\deltacp$. We find that a neutrino factory is the only instrument that can measure $\deltacp$ with a precision similar to that of its quark sector counterpart. All neutrino beams operating at peak energies $\gtrsim 2$ GeV are quite robust with respect to systematic uncertainties, whereas especially \bbeams and \thk suffer from large cross section uncertainties in the quasi-elastic regime, combined with their inability to measure the appearance signal cross sections at the near detector. A noteworthy exception is the combination of a $\gamma=100$ \bbeam with an \spl-based superbeam, in which all relevant cross sections can be measured in a self-consistent way. This provides a performance, second only to the neutrino factory. For other superbeam experiments such as \lbno and the setups studied in the context of the \lbne reconfiguration effort, statistics turns out to be the bottleneck. In almost all cases, the near detector is not critical to control systematics since the combined fit of appearance and disappearance data already constrains the impact of systematics to be small provided that the three active flavor oscillation framework is valid.

Process Plan Generation in Reconfigurable Manufacturing Systems using AMOSA and TOPSIS

Reconfigurable manufacturing system (RMS) is a recent manufacturing paradigm that responses to market changes cost-effectively. RMS consists mainly of reconfigurable machines, each of which has multiple configurations. In this paper we address the problem of process plan generation in RMS taking into account the multi-configuration nature of machines, in a multi-objective aspect. More specifically, we adapt AMOSA (Archived Multi-Objective Simulated Annealing) metaheuristic, to generate a set of non-dominated solutions, based on three criteria: completion time, total cost and reconfiguration effort. After that, TOPSIS method is used to rank these solutions in a preferential order.