A Periodicity Metric for Assessing Maintenance Strategies

Organised by: Cranfield UniversityThe maintenance policy in manufacturing systems is devised to reset the machines functionality in an economical fashion in order to keep the products quality within acceptable levels. Therefore, there is a need for a metric to evaluate and quantify function resetting due to the adopted maintenance policy. A novel metric for measuring the functional periodicity has been developed using the complexity theory. It is based on the rate and extent of function resetting. It can be used as an important criterion for comparing the different maintenance policy alternatives. An industrial example is used to illustrate the application of the new metric.Mori Seiki – The Machine Tool Company; BAE Systems; S4T – Support Service Solutions: Strategy and Transitio

Assessing the Complexity of a Recovered Design and its Potential Redesign Alternatives

Organised by: Cranfield UniversityReverse engineering techniques are applied to generate a part model where there is no existing documentation or it is no longer up to date. To facilitate the reverse engineering tasks, a modular, multiperspective design recovery framework has been developed. An evaluation of the product and feature complexity characteristics can readily be extracted from the design recovery framework by using a modification of a rapid complexity assessment tool. The results from this tool provide insight with respect to the original design and assists with the evaluation of potential alternatives and risks, as illustrated by the case study.Mori Seiki – The Machine Tool Compan

The evolution of molds in manufacturing: from rigid to flexible

Abstract Nowadays, dynamic products life cycles and increase in the number of product variants have led to reduction in demand per variant. This modern trend is in contrast with the high production volume of manufacturing processes such as injection molding, since they are commonly employed for mass production due to their long changeover time. Traditional rigid molds do not seem to be able to cope with the current industrial and market challenges. Flexible and reconfigurable molding processes, such as the discrete pin tooling systems and changeable molds, appear to be a promising choice for achieving manufacturing economic sustainability. They represent an effective way to save resources and reduce labor costs and setup times. This paper explores the evolution of molds used in manufacturing, from the old models to the current reconfigurable ones through a state-of-the-art analysis of academic research and solutions implemented by industry. Conclusions and insights are presented

Max-plus Modeling of Manufacturing Flow Lines

AbstractMax-plus algebra can be used to model manufacturing flow lines using linear state-space-like equations which can be used in analysis and control. This paper presents a method for easy and quick generation of the max-plus equations for manufacturing flow lines of any size or structure. The generated equations can model flow lines with infinite as well as finite buffer sizes.A flow line to be modeled is initially assumed to have infinite buffers for all stations. The line model equations are then generated as a combination of serial and merging stations after identifying the different stages using an adjacency matrix for the flow line. In the generated equations, the dynamics of the system are captured in two matrices that are function of the processing times of the different stations in the line. After generating these equations, extra terms are added to account for the finite buffers where for each buffer size, a matrix is added multiplied by the vector of system parameters delayed by the buffer size plus one.The method is intuitive and easy to understand and code in software and thus can facilitate quick analysis of different configurations of manufacturing flow lines and assessing what if scenarios. This can also allow quick on-line reconfiguration of controllers for frequently reconfiguring flow lines

Cost performance dynamics in lean production leveling

Balancing of production systems is one of the main lean manufacturing principles as it reduces in-process storage and related forms of waste. A dynamic systems approach is proposed to investigate challenges of implementing production leveling and associated costs. A lean cell producing at takt time is modeled using system dynamics. The model captures various lean tools influencing production leveling and their implications. Comparative cost analysis between various leveling implementation policies for stochastic demand with multiple products is conducted. Results showed that determining the most feasible leveling policy is highly dictated by both the cost and limitations of capacity scalability. In addition, delivery sequence plans of different products/parts needed to achieve mix leveling and lot sizes affect the feasible production leveling policy while implementing lean principles. The developed model and insights gained from the results can help lean manufacturing practitioners to better decide when and how to implement production leveling as well as determine both production lots sizes and sequence. They also emphasize the importance of cost analysis as assisting decision support tool in the trade-off required between the benefits of different levels of lean policies and their associated cost

Dynamic modelling of impact of lean policies on production levelling feasibility

A dynamic systems approach is proposed to investigate challenges of implementing production leveling and associated costs. A model of a lean cell is developed using system dynamics. The model captures various lean tools influencing production leveling. Comparative cost analysis between various leveling implementation policies for stochastic demand with multiple products is conducted. Results showed that determining the most feasible leveling policy is highly dictated by both capacity scalability cost and limitations. The developed model and revealed insights can help lean practitioners to better decide on when and how to implement production leveling as well as determine production lots sizes

Capacity management of modular assembly systems

Companies handling large product portfolio often face challenges that stem from market dynamics. Therefore, in production management, efficient planning approaches are required that are able to cope with the variability of the order stream to maintain the desired rate of production. Modular assembly systems offer a flexible approach to react to these changes, however, there is no all-encompassing methodology yet to support long and medium term capacity management of these systems. The paper introduces a novel method for the management of product variety in assembly systems, by applying a new conceptual framework that supports the periodic revision of the capacity allocation and determines the proper system configuration. The framework has a hierarchical structure to support the capacity and production planning of the modular assembly systems both on the long and medium term horizons. On the higher level, a system configuration problem is solved to assign the product families to dedicated, flexible or reconfigurable resources, considering the uncertainty of the demand volumes. The lower level in the hierarchy ensures the cost optimal production planning of the system by optimizing the lot sizes as well as the required number of resources. The efficiency of the proposed methodology is demonstrated through the results of an industrial case study from the automotive sector. © 2017 The Society of Manufacturing Engineer

Investigating optimal capacity scalability scheduling in a reconfigurable manufacturing system

Responsiveness to dynamic market changes in a cost-effective manner is becoming a key success factor for any manufacturing system in today’s global economy. Reconfigurable manufacturing systems (RMSs) have been introduced to react quickly and effectively to such competitive market demands through modular and scalable design of the manufacturing system on the system level, as well as on the machine components’ level. This paper investigates how RMSs can manage their capacity scalability on the system level in a cost-effective manner. An approach for modeling capacity scalability is proposed, which, unlike earlier approaches, does not assume that the capacity scalability is simply a function of fixed increments of capacity units. Based on the model, a computer tool that utilizes a genetic algorithm optimization technique is developed. The tool aids the systems’ designers in deciding when to reconfigure the system in order to scale the capacity and by how much to scale it in order to meet the market demand in a cost-effective way. The results showed that, in terms of cost, the optimal capacity scalability schedules in an RMS are superior to both the exact demand capacity scalability approach and the approach of supplying all required capacity at the beginning of the planning period, which is adopted by flexible manufacturing systems (FMSs). The results also suggest that the cost-effective implementation of an RMS can be realized through decreasing the cost of reconfiguration of these new systems