Developing a Capability-Based Similarity Metric for Manufacturing Processes

Author(s):  
Kevin Li ◽  
William Z. Bernstein

Manufacturing taxonomies and accompanying metadata of manufacturing processes have been catalogued in both reference books and databases on-line. However, such information remains in a form that is uninformative to the various stages of the product life cycle, including the design phase and manufacturing-related activities. This challenge lies in the varying nature in how the data is captured and represented. In this paper, we explore measures for comparing manufacturing data with the goal of developing a capability-based similarity metric for manufacturing processes. To judge the effectiveness of these metrics, we apply permutations of them to 26 manufacturing process models, such as blow molding, die casting, and milling, that were created based on the ASTM E3012-16 standard. Furthermore, we provide directions towards the development of an aggregate similarity metric considering multiple capability features. In the future, this work will contribute to a broad vision of a manufacturing process model repository by helping ease decision-making for engineering design and planning.

2020 ◽  
Vol 2020 ◽  
pp. 1-16 ◽  
Author(s):  
Atef M. Ghaleb ◽  
Husam Kaid ◽  
Ali Alsamhan ◽  
Syed Hammad Mian ◽  
Lotfi Hidri

The selection of manufacturing processes for a given application is a complex problem of multicriteria decision-making although there have been several different approaches that can be utilized to select a suitable alternative. However, identifying appropriate multicriteria decision-making approach from the list of available methods for a given application is a difficult task. This work suggests a methodology to assess different selection approaches, which are the technique for order of preference by similarity to ideal solution (TOPSIS), analytic hierarchy process (AHP), and VIKOR: stepwise procedure. This valuation was done depending on the following factors: number of alternative processes and criteria, agility through the process of decision-making, computational complexity, adequacy in supporting a group decision, and addition or removal of a criterion. A case study in this study was presented to analyse the evaluation methodology. The criteria used to evaluate and identify the best manufacturing process were categorized into productivity, accuracy, complexity, flexibility, material utilization, quality, and operation cost. Five manufacturing processes were considered, including gravity die casting, investment casting, pressure die casting, sand casting, and additive manufacturing. The results showed that each approach was suitable for the problems of manufacturing process selection, in particular toward the support of group decision-making and uncertainty modelling. Manufacturing processes were ranked based on their respective weights for AHP, TOPSIS, and VIKOR, and sand casting is the best. In terms of computational complexity, the VIKOR method performed better than TOPSIS and AHP. Moreover, the VIKOR and TOPSIS methods were better convenient to the selection of manufacturing processes for agility during the process of decision-making, the number of alternative processes and criteria, adequacy in supporting a group decision, and addition or removal of a criterion.


2010 ◽  
Vol 37-38 ◽  
pp. 1292-1295
Author(s):  
Yan Chao ◽  
Hai Feng Zhang ◽  
Li Qun Wu

Tolerance information plays a critical role in many steps of the product life cycle. It is especially important due to the advances in Internet technologies and increasing integration requirements from industry. In this paper, geometric tolerances information in manufacturing process (IMP) is studied, and the layered conformance level of geometric tolerances is established according to ASME Y14.5-1994, STEP and DMIS. An EXPRESS-G data model of geometric tolerance information in IMP is established. The XML language is used to represent and program the geometric tolerances information in IMP.


Author(s):  
Paul Witherell ◽  
Shaw Feng ◽  
Timothy W. Simpson ◽  
David B. Saint John ◽  
Pan Michaleris ◽  
...  

In this paper, we advocate for a more harmonized approach to model development for additive manufacturing (AM) processes, through classification and metamodeling that will support AM process model composability, reusability, and integration. We review several types of AM process models and use the direct metal powder bed fusion AM process to provide illustrative examples of the proposed classification and metamodel approach. We describe how a coordinated approach can be used to extend modeling capabilities by promoting model composability. As part of future work, a framework is envisioned to realize a more coherent strategy for model development and deployment.


Author(s):  
Mostefai Abdelkader

Process model matching is a key activity in many business process management tasks. It is an activity that consists of detecting an alignment between process models by finding similar activities in two process models. This article proposes a method based on WordNet glosses to improve the effectiveness of process model matchers. The proposed method is composed of three steps. In the first step, all activities of the two BPs are extracted. Second, activity labels are expanded using word glosses and finally, similar activities are detected using the cosine similarity metric. Two experiments were conducted on well-known datasets to validate the effectiveness of the proposed approach. In the first one, an alignment is computed using the cosine similarity metric only and without a process of expansion. While, in the second experiment, the cosine similarity metric is applied to the expanded activities using glosses. The results of the experiments were promising and show that expanding activities using WordNet glosses improves the effectiveness of process model matchers.


2019 ◽  
Vol 11 (9) ◽  
pp. 2560
Author(s):  
Hyun Ahn ◽  
Tai-Woo Chang

As the adoption of information technologies increases in the manufacturing industry, manufacturing companies should efficiently manage their data and manufacturing processes in order to enhance their manufacturing competency. Because smart factories acquire processing data from connected machines, the business process management (BPM) approach can enrich the capability of manufacturing operations management. Manufacturing companies could benefit from the well-defined methodologies and process-centric engineering practices of this BPM approach for optimizing their manufacturing processes. Based on the approach, this paper proposes a similarity-based hierarchical clustering method for manufacturing processes. To this end, first we describe process modeling based on the BPM-compliant standard so that the manufacturing processes can be controlled by BPM systems. Second, we present similarity measures for manufacturing process models that serve as a criterion for the hierarchical clustering. Then, we formulate the hierarchical clustering problem and describe an agglomerative clustering algorithm using the measured similarities. Our contribution is considered on the assumption that a manufacturing company adopts the BPM approach and it operates various manufacturing processes. We expect that our method enables manufacturing companies to design and manage a vast amount of manufacturing processes at a coarser level, and it also can be applied to various process (re)engineering problems.


Author(s):  
László Horváth ◽  
◽  
Imre J. Rudas ◽  

This paper presents a novel methodology for modeling manufacturing processes of mechanical parts. The aim was to develop a manufacturing process model that describes all possible process variants in a single model and involves generic process description for a cluster of manufacturing tasks. It must be fit into the product model concept. A four-level generic manufacturing process model has been developed by using Petri net representation for model entities. Advanced shape models do not describe the intent of the designer and other information that is necessary for the application of the model. As a contribution to solving this problem, we propose a methodology for attaching designer intent information and knowledge to geometric and form feature models. This improves communication between the product designer and production engineer. First, the importance of the manufacturing process model and its interconnections with other product related models are emphasized. Then, the structure, entities, creating, evaluation, and application of the manufacturing process model are explained. Next, product and production process modeling procedures are analyzed from the point of view of design intent information to be transferred between product designers and manufacturing engineers. Finally, characteristics of communication between engineers and modeling of human intent are outlined.


Author(s):  
Matteo M. Smullin ◽  
Zahra Iman ◽  
Karl R. Haapala

Life cycle assessment software packages such as SimaPro, GaBi, and Umberto have become well-established tools for conducting environmental impact analysis. However, applications for broader sustainability assessment are limited. Recent research has developed an information modeling framework to compose models of unit manufacturing processes for sustainability assessment and has led to the definition of unit manufacturing process information modeling concepts. An engineer can use the framework to conduct manufacturing system-level sustainability assessments by composing models of unit manufacturing processes. Assessment results can aid engineers in selecting the superior manufacturing process flow for a given product. To demonstrate usefulness of the information framework, a prototype desktop application has been developed. The application was implemented in Windows Project Foundation (WPF) using C# as the coding language to create a graphical user interface. Mathworks MATLAB serves as the calculation engine. Unit manufacturing process models follow the framework and are read by the application, which produces a sustainability assessment for the manufacturing process flow. A manufacturing process flow for an automobile-like metal product acts is used to demonstrate the software application.


Processes ◽  
2018 ◽  
Vol 6 (10) ◽  
pp. 179 ◽  
Author(s):  
Axel Schmidt ◽  
Maximilian Sixt ◽  
Maximilian Huter ◽  
Fabian Mestmäcker ◽  
Jochen Strube

Liquid-liquid extraction (LLE) is an established unit operation in the manufacturing process of many products. However, development and integration of multistage LLE for new products and separation routes is often hindered and is probably more cost intensive due to a lack of robust development strategies and reliable process models. Even today, extraction columns are designed based on pilot plant experiments. For dimensioning, knowledge of phase equilibrium, hydrodynamics and mass transport kinetics are necessary. Usually, those must be determined experimentally for scale-up, at least in scales of DN50-150 (nominal diameter). This experiment-based methodology is time consuming and it requires large amounts of feedstock, especially in the early phase of the project. In this study the development for the integration of LLE in a new manufacturing process for artemisinin as an anti-malaria drug is presented. For this, a combination of miniaturized laboratory and mini-plant experiments supported by mathematical modelling is used. System data on extraction and washing distributions were determined by means of shaking tests and implemented as a multi-stage extraction in a process model. After the determination of model parameters for mass transfer and plant hydrodynamics in a droplet measurement apparatus, a distributed plug-flow model is used for scale-up studies. Operating points are validated in a mini-plant system. The mini-plant runs are executed in a Kühni-column (DN26) for extraction and a packed extraction column (DN26) for the separation of side components with a throughput of up to 3.6 L/h, yield of up to 100%, and purity of 41% in the feed mixture to 91% after washing.


Author(s):  
Christer P Karlsson ◽  
Anders Avelin ◽  
Erik Dahlquist

The implementation of model-based control and diagnostics suffer strongly from the fact that models deteriorate as a function of process and sensor deterioration. Also, changes in the raw material (i.e. wood) may occur and often the process control is not addressing these variations in reality. It is thus vital for the model system to be robust in the sense that it is transparent and easy for the operator to maintain. Robustness is essential in many parts of the system, including measurement, process model validation, the ability of the model to adapt to changes in the process, optimization algorithms, and of course the model itself. In this paper, we first show three real-life applications of the utilization of models for diagnostics and control. Thereafter conditions for on-line adaptation of the models are discussed. The challenges when designing such a system are in achieving operator confidence, filtering of misleading measured data, adaptation of process parameters when the process parameters change, and combining validation of measurements and process models. These challenges are met by using a combination of physical and statistical models and methods based on them such as model predictive control (MPC) and parameter estimation. The model should be maintained by a qualified engineer who should be able to explain the system to the operator so that it is understood and confidence can be maintained.


Author(s):  
Ana Pego ◽  
Maria do Rosário Matos Bernardo

Decision making is an important role performed by managers. This chapter will analyze the importance of information systems (IS) on the decision-making process at rural organizations in Portugal's Algarve region. Managers' perceptions were analyzed and compared with the decision-making process model proposed in this chapter, which was based on the models of Simon (1977) and Mintzberg, Raisinghani, and Theorêt (1976). This chapter will discuss the capacity of rural tourism organizations to solve problems, as well as review the time needed to solve problems through the use of IS. This chapter will conclude that IS in the organizational decision-making process is positively related to the identification of the decision-making problem and time needed to solve the problems. This investigation will allow other sectors the opportunity to discuss decision process models based on technology, information capability, and organizational competitiveness.


Sign in / Sign up

Export Citation Format

Share Document