Production System Design Process Research Articles

A specification language for automated design space exploration of production systems

Integrating simulation in the design process of production systems allows the predicted performance of design alternatives to be compared. However, many iterations of specifying the design, constructing the simulation model, performing simulation experiments, and evaluating the simulation results for each (re)design are required. The process of specifying, modelling, simulating, and evaluating a design can be automated using a framework for automated design space exploration of production systems. This paper presents a formal specification language for the design space of a production system topology. Using the specification of the design space, feasible designs can be generated. The language supports the specification of component types, component instances, and constraints such as how many instances of a type are allowed and how components are allowed to be connected. The specification language is validated through an adaptation of an industrial case study.

Enablers in the production system design process impacting operational performance

ABSTRACT This paper explores how the design process of the production system could be utilized to improve the operational performance during the production ramp-up and operation phases. A qualitative case study was carried out in a large process-type manufacturing company, focusing on three new production line launching projects. Different actions taken in the design process of the production lines were linked to their impact during the running operation phase and operational performance, which is measured by the metric of Overall Equipment Effectiveness (OEE) within lean manufacturing. The empirical findings provides a concrete example that activities in the design process impact on the OEE. A set of enablers in the production system design process at different systems-level, especially concerning the acquisition of new production equipment have been demonstrated that has potential to achieve the target operational performance. Finally, the concept of operational performance driven production system design process is proposed.

A Knowledge Based System for Managing Heterogeneous Sources of Engineering Information

Abstract As ever increasing amounts of engineering information become available, engineers require novel ways to manage this information. Especially in mechatronic engineering, e.g., the engineering of Cyber-Physical Production Systems, engineers from various disciplines are involved, and they represent their knowledge in heterogeneous ways. To be able to efficiently gain an overview of the available information and find the information required, engineers need support. Additionally, awareness regarding interdisciplinary dependencies should be increased to reduce late changes. Such dependency analyses allow engineers to better identify and thus manage potential inconsistencies, which can be expected to reduce development time. The Knowledge Based System presented supports engineers during the design process of production systems by providing an overview of available engineering knowledge, its representation, and associated stakeholders. Additionally, engineers can leverage the underlying holistic information model to create and manage digital twins.

Exploring the design process of reconfigurable industrial production systems

PurposeThe purpose of this paper is to explore activities, challenges, and suggest tactics for the design of industrial reconfigurable production systems that can easily adapt to changing market opportunities.Design/methodology/approachThe paper synthesizes the empirical findings of seven case studies including 47 in-depth interviews at four manufacturing companies.FindingsA conceptual production system design process and including activities that enables a long-term perspective considering reconfigurability is proposed. Additionally, critical challenges indicating that reconfigurable production system design is not a trivial issue but one that requires separate control and coordination are identified and tactics to overcome the challenges described.Research limitations/implicationsThe authors propose a process for designing reconfigurable production systems that are better suited to adjust to future needs. The knowledge of reconfigurability from the reconfigurable manufacturing system literature is applied in the general production system literature field. This study contributes to a clearer picture of managerial challenges that need to be dealt with when designing a reconfigurable production system.Practical implicationsBy clarifying key activities facilitating a long-term perspective in the design process and highlighting challenges and tactics for improvement, the findings are particularly relevant to production engineers and plant managers interested in increasing the ability to adapt to future changes through reconfigurability and improve the efficiency of their production system design process.Originality/valueAlthough reconfigurable production systems are critical for the success of manufacturing companies, the process of designing such systems is not clear. This paper stretches this by giving a comprehensive picture of the production system design process and the activities that need to be considered to meet these challenges.

Improving Lean Design of Production Systems by Visualization Support

The design process of production systems is complex with many different aspects to consider for efficiently developing and installing an effective system. Important success factors during the design process are typically the abilities to identify and manage risks, develop mitigation plans, and conduct timely proactive problem solving. The work reported in this paper is part of research addressing methods for how the design process can be supported by using virtual representations of the factory environments captured with 3D laser scanning. This support is evaluated in an industrial study of one industrialization project in the manufacturing industry. The industrialization project follows the process to design layout, work places, and plan for installation of new equipment to create a production system within a refurbished shop floor area. The area will include CNC machining centers, welding stations, product inspection, product cleaning, and material handling. 3D laser scanning is used to provide an accurate and realistic virtual representation of the current shop floor area. This virtual representation is combined with 3D CAD models of the new machining centers and other equipment to provide a realistic visualization of the planned production system. The research approach and its questions investigate the benefits of combining the lean principles to design and development of production systems using a realistic visualization, which include systematic risk analysis and problem solving as important activities. The result shows that visualization support gave a great advantage to identify the possible risks and problems, which resulted in higher confidence and substantial timesaving in planning and execution of the industrialization project.

Process mapping as a tool for participative integration of human factors into work system design

In this study, we develop and evaluate a method for applying business process mapping to document the production system design process (PSDP) within an electronics manufacturer. We then test the ability of the map to facilitate identification of opportunities to integrate human factors (HF) proactively into the company’s PSDP. Stakeholders (n = 31) from various departments were involved in recorded interviews and workshops (109 hours over 20 months) at three stages: map creation, map application, and evaluation of the mapping process. Map application resulted in stakeholders identifying 13 opportunities to integrate proactive human factors into specifically mapped points of the PSDP. The map allowed participants to see the flow of activities and information from a higher level. Methodological issues to resolve in undertaking a PSDP include definition of scope and level of mapping detail, content errors, missing information, and map overlap.

Characteristics affecting management of design information in the production system design process

Although it has been argued that the design of production systems is crucial, there is a general lack of empirical studies analysing and identifying resources and capabilities required for an efficient production system design process. One of these resources is the critical role attributed to design information and one such capability is how the design information is managed. To address this research gap, this paper reports the results from two in-depth case studies in the automotive industry focusing on the management of design information in the production system design process. Our results show that design information management needs to be understood as a multidimensional concept having three dimensions: acquiring, sharing and using design information. By focusing on the three dimensions, six characteristics affecting the management of design information when designing the production system are identified. The characteristics are information type, source of information, communication medium, formalisation, information quality and pragmatic information.

Reconfigurable production system design – theoretical and practical challenges

Purpose – The purpose of this paper is to explore theoretical and practical challenges to achieve reconfigurable production system designs. Design/methodology/approach – The empirical material of this paper includes a multiple-case study with an embedded design (Yin) including four cases, where each case represents a production system design project. The consideration of reconfigurability and its characteristics in the production system design projects was studied. To enhance validity, two real-time studies were combined with two retrospective studies (Leonard-Barton). Findings – For more than a decade foresight reports have pointed out the need for responsiveness to change through reconfigurability in production system design. In order to achieve reconfigurable production systems, three challenges were identified: to use a structured design methodology, to gain knowledge in reconfigurability and its characteristics, and to include the reconfigurability knowledge in a structured design methodology. Still there is no comprehensive support available for reconfigurability in the production system design process. Research limitations/implications – Limitations are mostly related to the chosen methodology approach, and additional empirical studies to establish generic results are required. Practical implications – By combining knowledge from the production system design field with the reconfigurable manufacturing system field a potential of meeting identified challenges is pointed out. Originality/value – This paper adds to current knowledge by pointing out three main challenges to achieving reconfigurable production systems. The paper also contributes with ideas on how to respond to these challenges.

MAPPING ENGINEERING DEVELOPMENT PROCESSES FOR PROCESS IMPROVEMENT

Integrating human factors considerations into the design of production systems can improve productivity and quality results while reducing injury risks to system operators. The researchers are currently conducting an action research study with a Canadian electronics manufacturer to improve their production system design process (PSDP), and thereby their production systems, by integrating human factors (HF). One of the first requirements is a clear understanding of the PSDP as a means of identifying and coordinating process improvements. Since there is no accepted approach to PSDP ‘mapping’, methodological development is needed. A proposed methodology for assessment of PSDPs is described. Data collection includes a combination of interview, observational, and document sources. Analysis uses a general inductive approach to develop a process ‘map’. Mapping options to be assessed for utility include decision trees, cross-functional diagrams, actor-network analyses and concept maps. The developed map will then be verified by company personnel and subsequently used in developmental workshops to help the design team identify possible process improvements. As part of the ‘action research’ methodology, researchers will make observations and field notes to better understand how such process maps can best be created and communicated to company personnel. Challenges include gaining access to confidential company data, and experience shows that the active participation of company personnel in data collection speeds and enhances this process. The utility of the PSDP maps to support process improvement efforts remains to be studied.

Performance evaluation of production systems monitored by statistical process control and off-line inspections

Quality and productivity performance measures are very often considered in separate phases of the production system design process. However, the production system architecture affects the efficiency of the quality control system as well as the quality control configuration has an impact on the performance of the production system. The paper proposes a new analytical method for evaluating the performance of production systems in which statistical process control (SPC) techniques are implemented. Machines behaviour is monitored by measuring quality characteristics of the produced parts through off-line inspection devices and sampling inspections. The numerical results show the good accuracy of the proposed method, provide new insight in the relations among the two areas and pave the way to the joint design of production logistics and quality control systems.

Design-to-Cost for Production Systems

The objective of cost modeling is to evaluate the costs of a product and how these costs are likely to alter with changes to the system design, product components and processes. Specifically, this includes the breaking down and ranking of cost into its core elements. While manufacturing costs are essential to product system evaluation, performance subsequent to customer requirements needs also to be considered. Design-to-Cost for Production Systems presents a generic methodology to combine cost modeling and Quality Function Deployment in order to assess the potential trade-off between cost and performance for competing product alternatives at the early stage of the production system design process.