Identifying Improvement Areas in Production Planning Meetings by Assessing Organisation and Information Systems at a Small Production Company

The increased mass-customisation of production requires operators to manage an increasing number of complex work tasks. From a social sustainability perspective, better sharing and dissemination of production information supports operators cognitively to manage and understand their work tasks, which in turn improves quality of work. So, the focus of this paper is to study how production planning meetings can be improved. Previous research suggests that the MEET model can be used as a framework for improving meetings and information sharing by studying 10 different areas within a company’s Organisation System (OS) and Information System (IS) whilst considering the time and place prerequisites and aims for these meetings. In this paper, the applicability of the MEET model and its 10 areas are tested at a small production company by applying two different approaches. First, a questionnaire was presented to and filled out by a manager, the results of the questionnaire identifies the improvement potential of each of the 10 areas. Second, a comprehensive current-state analysis based on observations on the shop-floor and interviews with operators were carried out with regards to the 10 areas. The results from these two approaches were compared and the comparison showed that both approaches point towards similar areas for potential improvements. This paper concludes that the MEET model can be used as a general framework to inspire change by suggesting areas with potential improvement in information sharing. While the selfassessment questionnaire can identify a direction, additional information and involvement of other stakeholders are recommended for actual implementations of change. For future research, the methods based on the MEET model will be further developed to improve accuracy and the suggestions provided to the case company in this paper will be tested as a validation of the model

Prioritisation of root cause analysis in production disturbance management

Purpose: Manufacturing companies struggle to manage production disturbances. One step of such management deals with prioritising those disturbances which should undergo root cause analysis. The focus of this work is on two areas. First, investigating current challenges faced by manufacturing companies when prioritising root cause analysis of production disturbances. Second, identifying the stakeholders and factors impacted by production disturbances. Understanding the current challenges and identifying impacted stakeholders and factors allows the development of more efficient prioritisation strategies and, thus, contributes to the reduction of frequency and impact of disturbances. Design/methodology/approach: To achieve the intended purpose of this research, a qualitative approach was chosen. A series of interviews was conducted with practitioners, to identify current challenges. A series of focus groups was also held, to identify the impacted stakeholders and factors by disturbances. Findings: Various challenges were identified. These are faced by manufacturing companies in their prioritisation of production disturbances and relate to the time needed, criteria used, centralisation of the process, perspective considered and data support. It was also found that a wide range of stakeholders is impacted by production disturbances, surpassing the limits of production and maintenance departments. Furthermore, the most critical factors impacted are quality, work environment, safety, time, company results, customer satisfaction, productivity, deliverability, resource utilisation, profit, process flow, plannability, machine health and reputation. Originality/value: The current situation regarding root cause analysis prioritisation has not been identified in previous works. Moreover, there has been no prior systematic identification of the various stakeholders and factors impacted by production disturbances

Digital Tools and Information Needs Assessment for Efficient Deviation Handling in SMEs

A shift to digitalization implies a high emphasis on both management and creation of data. In a time of change, when high emphasis is put on the application of technology, there is a high risk that too little is said about the compliance of internal needs. Companies and practitioners risk to not prioritizing the assessment and questioning the adoption of digital ways of working. The present paper intends to discuss the impact that digital tools may have on deviation management in Small to Medium Size Enterprises (SMEs) and under which circumstances digital tools will improve deviation management in SME context. The research study employs a qualitative approach using the case study methodology. The source of data comes from five different manufacturing companies categorized as SMEs, mainly doing business in the automotive and maritime industry. A multidisciplinary team performed semi-structured interviews and fieldwork at each site, along with regular online meetings with all the partners. The study employs five dimensions from the information quality perspective to assess information utilized to support deviation handling and then connects the information quality deficiencies to the digital tools impact. The empirical data indicate the need for the companies to perform a requirement analysis, as a prerequisite for them to assess their current state in terms of data and information, before the adoption of digital systems or digital tools. The research demonstrates the value for SMEs to understand their information needs and usage, in order to better determine their data needs and how to translate data into information. Lastly, this paper intends to provide a better foundation for SMEs prior to investments on automation and digitalization in the area of disturbance handling on the production shop floor

Validation of the complexity index method at three manufacturing companies

In order to manage increasing numbers of product variants, tools that can reduce or manage production complexity are vital. The paper describes CompleXity Index (CXI), an index-based method and tool that assess the complexity and difficulty of work at an industrial workstation. CXI was validated at three Swedish manufacturing companies studying the correctness of the calculation, usage as a prediction tool and the view of different roles. In all three cases, CXI was seen as a useful tool to evaluate the operator-perceived complexity of a workstation

Dealing with resistance to the use of Industry 4.0 technologies in production disturbance management

Purpose: Resistance is expected to emerge with the implementation and use of new technologies in production systems. This work focuses on identifying sources of resistance to the use of Industry 4.0 technologies when managing production disturbances and suitable managerial approaches to deal with them. Design/methodology/approach: A qualitative approach was chosen in this research. The authors conducted a literature review and a series of interviews. Thirty-one papers from the literature review were analysed, and 16 people from five different companies were interviewed. Findings: The authors identified five different sources of resistance and three managerial approaches to dealing with them. The sources of resistance were based on (1) feelings of over-supervision, (2) unclear values, (3) feelings of inadequacy, (4) concerns about loss of power and jobs and (5) work overload. The three approaches to dealing with resistance are (1) communication, (2) participation and (3) training. Originality/value: This work identifies the sources and strategies to deal with resistance to the use of Industry 4.0 technologies in the management of production disturbances. The managerial literature in this area is limited, and to the authors\u27s knowledge, the specific sources for resistance and strategies to deal with that in this topic have not been systematically investigated before

MEETINGS – THE INNOVATIVE GLUE BETWEEN THE ORGANISATION SYSTEM AND INFORMATION SYSTEM

The research presented aims for enhanced utilization of human skills, collaboration, and information sharing. This paper concerns the production context, and the needs and challenges of people striving for high-quality, innovative, and efficient work. The paper presents a model of the information system (IS) and organisations system (OS) and their integration. Main conclusions are that these systems overlap, and create an innovative working arena for the different working processes. People with knowledge gather into meetings held for different purposes supported by technical systems. These meetings provide a core element for efficient and innovative collaboration, requiring parallel development of IS and OS

SMARTARE M 6TEN MEET-MODELLEN

Smartare m\uf6tenmed MEET-modellenMEET-modellen bidrar till ett mer strukturerat arbeteg\ue4llande organisations- och informationsstruktur n\ue4rolika former av m\uf6ten skall planeras.M\ue5let \ue4r effektivare m\uf6ten, b\ue4ttre v\ue4gval g\ue4llandeorganisatoriska och informatoriska fr\ue5gor, \uf6katinformations- och kunskapsspridande i organisationensamt att g\ue5 fr\ue5n individuellt till organisatoriskt l\ue4rande

A tool for holistic assessment of digitalization capabilities in manufacturing SMEs

In a constantly evolving global market, manufacturing companies need to be flexible and adaptive to survive. Digital twins of production systems have been proposed as one part of the solution, however this comes with multiple challenges. Manufacturing SMEs have limited resources and need to direct their efforts in this area wisely. This paper presents a tool for holistic assessment of an SME manufacturer\u27s level of digitalization, in order to visualize current gaps and guide digitalization efforts over a production system\u27s life cycle. The tool was empirically developed together with Manufacturing SMEs and has strengthened their digitalization awareness and capabilities

Supporting Individual Needs for Intra-Organisational Knowledge Sharing Activities in Pre-Industry 4.0 SMEs

The complexity of modern manufacturing industry and the emergence of Industry 4.0 puts changing cognitive demands on human operators at work. Operators in this environment, Operator 4.0, will share knowledge through the use of new digital technologies that should be implemented in parallel with an organizational development towards Organization 4.0. On an individual level within the organization, people benefit from understanding their own knowledge needs and gain necessary knowledge through knowledge sharing activities. In pre-Industry 4.0 organizations, this is done primarily through meetings. Originally developed to create smart meetings in smart factories, an elaborated version of the MEET model (Gullander et al, 2014) is used in this paper to evaluate the needs for sharing of tacit and explicit knowledge, both in regards to how it affects the Information System and the Organization System. By adding a systematic process approach to mapping individual knowledge needs related to production activities, these needs can be identified for each process step. By using this systematic approach to apply the MEET model, two Swedish SMEs within the manufacturing industry have developed their knowledge sharing activities. This human-centred study, based on questionnaires and interviews, focuses on how shop-floor operators perceive changes in knowledge sharing activities due to the use of the MEET model. Novelty in this research lies in the attempt to link the technology-intensive Industry 4.0 development with an organizational emphasis. Results show that the applied method can be used to pragmatically improve knowledge sharing from certain aspects, but further research is required to determine the correlation between different areas and their effect on knowledge sharing. This paper suggests that knowledge sharing in organizations can be benefitted from Industry 4.0 enabling technologies, introducing this as Organization 4.0

On Reference Architectures for Development of Flexible Cell Control Systems

Industrial problems of inflexible and expensive shop-floor control systems were analysed. The principal causes are suggested to be poor development methodology, poor tools used for development and implementation, and poor knowledge on how such systems are best built. This work mainly focuses on providing industry with better knowledge on how shop-floor control systems should be designed. It is suggested that this knowledge should be collated to form a generic reference architecture to be used as a template for the development process. The conclusions drawn from four case studies, literature, and industrial surveys relate to two areas.<p /> First, a template for the definition of reference architectures has been defined. It specifies that the reference architectures should be simple to understand and to use, and fit the needs of the industry concerning system properties, functions, and genericity. Furthermore, they should provide support to the engineers in managing the complexity of the system and of the development process. Therefore, they should be accompanied with a description of how one should develop a design specification for a specific system from a generic reference architecture and how to implement the system based on this specification. Reference architectures should specify the control system's functions, structure, behaviour, and information.<p /> Secondly, Chalmers Reference Architecture and Methodology for Flexible Production Systems, CHAMP, was developed with a primary focus to achieve high flexibility for the computer-based scheduling, control, monitoring, and error handling activities in manufacturing cells. The main features are the generic control logic, the use of a central database, the separation of product operation lists from the description of resource capabilities, and the automatic synthesis of product operations with resource capabilities. This thesis reports on research on specific parts of CHAMP: (i) the modular control structure and the generic message-passing scheme by which the modules cooperate, (ii) the separation of generic and specific control activities, (iii) the definition of generic resource models, and (iv) the definition of data regarding manufacturing resources and error-handling. The genericity of the whole reference architecture has been validated by industrial surveys, in which CHAMP was conceptually applied to various types of manufacturing cells in Swedish industry