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To date, the literature has usually assumed that a universal approach to resilience is appropriate in which different resilience capabilities are equally important for all organizations independent of contextual characteristics. In contrast this study investigates if production process characteristics affect resilience capabilities in terms of redundancy, flexibility, agility and collaboration.

An in-depth exploratory multiple case study was carried out in eight companies across different industries. Data were gathered through multiple interviews with key informants in each company.

The authors find differences in, and trade-offs between, resilience capabilities and practices related to redundancy, agility and collaboration induced by the different configurations of production system characteristics: especially between discrete and process industries. Further, a major influential characteristic is the production strategy employed (make-to-stock or make-to-order) which stresses or limits collaboration and redundancy.

This is one of the first studies to explore the effects of production system characteristics as a major contingency factor on the resilience capabilities of an organization. As such it provides valuable insights into the development of a more nuanced contingency approach to how organizations can build resilience and employ specific practices that fit their situation.

The purpose of this paper is to explore theoretical and practical challenges to achieve reconfigurable production system designs.

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).

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.

Limitations are mostly related to the chosen methodology approach, and additional empirical studies to establish generic results are required.

By combining knowledge from the production system design field with the reconfigurable manufacturing system field a potential of meeting identified challenges is pointed out.

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.

Evolvable production systems enable fully reconfiguration capabilities on the shop floor through process‐oriented modularity and multi‐agent‐based distributed control. To be able to benefit architectural and operational characteristics of evolvable systems, there is a need of a new planning approach which links shop floor characteristics and planning operations. This paper seeks to address these issues.

Evolvable production system has a structured methodology in itself. Consistent to this, a reference planning architecture is developed aiming to achieve agility on planning activities. Besides a workload control method is proposed and implemented as a part of the planning architecture.

First applications of evolvable systems have been implemented through European research projects. Shop floor working principles and architectural characteristics are consistent to facilitate more agility on planning activities which are framed at a planning reference architecture called demand responsive planning. As an implementation case, an agent‐based workload control method is proposed and implemented. The characteristics of EPS and proposed planning architecture enable continuous and dynamic workload control of the shop floor to be implemented.

This paper presents a new planning model compatible with evolvable production systems targeting to agility to demand on planning and control activities benefiting shop floor enhancements of a fully reconfigurable system which enables to relax constraints imposed from production systems to planning. In addition, a continuous and dynamic workload control method is proposed and implemented.

Presents a classification for production systems in manufacturing and processing industries. The proposed classification is intended to enlarge the scope of production systems that can be meaningfully classified. This is accomplished by including production system properties used in previous classifications and incorporating new characteristics that describe major changes in emerging automated production systems. The proposed classification is intended to provide better understanding of the functioning of production systems and management approaches available to improving their processes.

Part of a research programme being undertaken in Italy on the applicability of the just‐in‐time (JIT) approach. The programme includes both the development of methodological concepts to evaluate JIT applicability and an extensive survey of the value of JIT implementation as seen by Italian industry. Two levels of performances are identified: o First, the various performances at system level (critical manufacturing tasks) where the dimensions and measurement of productivity, service, quality and flexibility are defined; o Second, “operating conditions” being the variables describing the characteristics of single production factors and their interconnection (such as efficiencies, capability, process flexibility and lead times) The set of JIT techniques in the area of product, process, organisation, planning and control and supply are classified, the ways the techniques impact on operating conditions and, through them, on performance at production system level are analysed. A paradigm of JIT approach results, which explains the changes in the traditional trade‐offs within overall performance.

In the current competitive environment, each company faces a number of challenges: quick response to customers’ demands, high quality of products or services, customers’ satisfaction, reliable delivery dates, high efficiency, and others. As a result, during the last five years many firms have proceeded to the adoption of enterprise resource planning (ERP) solutions. ERP is a packaged software system, which enables the integration of operations, business processes and functions, through common data‐processing and communications protocols. However, the majority, if not all, of these systems do not support the production scheduling process that is of crucial importance in today’s manufacturing and service industries. In this paper, the authors propose a knowledge‐based system for production‐scheduling that could be incorporated as a custom module in an ERP system. This system uses the prevailing conditions in the industrial environment in order to select dynamically and propose the most appropriate scheduling algorithm from a library of many candidate algorithms.

The purpose of this paper is to estimate the required number of robots consisting of some non-repairable components, by employing a renewal model. Considering the importance of the availability of standby autonomous robots for reducing and preventing down-times of advanced production systems, which imposes a considerable loss, the present research tries to introduce a practical model for the determination of the required number of autonomous robots.

Most of the available research on the estimation of the required standby components based on the reliability characteristics of components has not considered the environmental factors influencing the reliability characteristics. Therefore, such estimations are not accurate enough. In contrast, this paper focuses on the influence of the environmental and human factors (e.g. the operators’ skill) on the robot reliability characteristics.

A model based on the Weibull renewal process combined with the cold standby strategy is developed for reliability evaluation of the system. The effectiveness of the proposed integrated reliability evaluation model is worked out in some cases.

Determining a required number of robots is an important issue in availability and utilization of a complex robotic production system. In an advanced production system, while the estimation process of a required number of robots can be performed through different approaches, one of the realistic estimation methods is based on the system’s reliability that takes into consideration the system operating environment. To forecast the required number of robots for an existing production system, in some cases, the assumption of a constant failure rate does not differ much from the assumption of a non-constant failure rate and can be made with an acceptable error.

During design of reconfigurable manufacturing systems, manufacturing companies need to select and implement the right enablers of reconfigurability in accordance with the specific requirements being present in the manufacturing setting. Therefore, the purpose of this paper is to investigate enablers of reconfigurability in terms of their importance in industry, current level of implementation in industry, and significant differences in their implementation and criticality across different manufacturing settings.

A questionnaire survey is conducted, in order to provide generalizable empirical evidence across various industries and manufacturing types.

The findings indicate that the level of implementation of the reconfigurability enablers is rudimentary, while their criticality is perceived higher than the current level of implementation. Moreover, significant differences regarding implementation and criticality of mobility, scalability, and convertibility were found for companies with varying degrees of manual work, make-to-stock production, and varying production volume, industry type and organization size.

Main limitations of the research cover the relatively small sample size and non-random sampling method applied, primarily limited to one country, which could be increased to further extent the findings reported in this paper.

The findings indicate that the importance and implementation of reconfigurability enablers is contingent on the manufacturing setting. Thus, the research presented in this paper provides valuable knowledge in regard to aiding a paradigm shift in industry and help companies design manufacturing systems with the right reconfigurability enablers.

This paper expands research on manufacturing system design for changeability and reconfigurability, by explicitly considering these as capabilities that can be enabled in various ways for various purposes in different manufacturing contexts.

Structures the concept of flexibility by making clear distinctions in three generic dimensions, describes the use of the framework for manufacturing flexibility by working through a concrete example. The framework was presented in “Making manufacturing flexibility operational – part 1: a framework”, IMS, Vol. 6 No. 2. Makes distinctions between the concept of flexibility in the three generic dimensions: utilized flexibility versus potential flexibility, external flexibility versus internal flexibility, and requested flexibility versus replied flexibility. The framework makes a clear distinction between the internal and the external factors impinging on the company, and brings together the market demand for flexibility, the characteristics of the production system, and the flexibility of the suppliers. Furthermore, pursues the connection from the strategic level to the single resource characteristics in the production system. Using the framework as a systematization for handling flexibility related issues in companies, can be especially useful for managers.

The purpose of the paper is to present an integrated methodology for identifying effective economic incentives to enhance quality performance by mango producers in Costa Rica.

The study analyses the relationship between intrinsic product quality attributes and socio‐economic characteristics of mango producers in the Central Pacific zone of Costa Rica. Data are derived from a representative sample of 35 mango producers. A mango quality index for local and export market outlet is constructed and quality performance is subsequently related to farm‐household characteristics and contractual delivery parameters. Categorical regression methods are used to identify the relationships between farm‐household characteristics, production system features, marketing relationships and quality attributes weighted by consumers' preferences.

Key attributes of the quality index – related to dimensions of ripeness, appearance and variability – appear to be strongly related to farm‐household characteristics like the producers' age and experience, input use intensity and family labour availability. Preferences for certain contractual regimes and marketing arrangements give rise to differentiation in quality performance. Long‐term delivery relationships and non‐price attributes appear as key factors for quality improvement in mango.

Although the study is based on a modest sample, the significant relationships between the constructs in the model are found to be sufficiently robust.

The research approach enables the estimation of a model where quality performance is related to technical and institutional aspects related to the organisation of mango delivery chain.