Aspects of the design and operation of production control systems in manufacturing industry

Computerised production control developments have concentrated on Manufacturing Resources Planning (MRP II) systems. The literature suggests however, that despite the massive investment in hardware, software and management education, successful implementation of such systems in manufacturing industries has proved difficult. This thesis reviews the development of production planning and control systems, in particular, investigates the causes of failures in implementing MRP/MRP II systems in industrial environments and argues that the centralised and top-down planning structure, as well as the routine operational methodology of such systems, is inherently prone to failure. The thesis reviews the control benefits of cellular manufacturing systems but concludes that in more dynamic manufacturing environments, techniques such as Kanban are inappropriate. The basic shortcomings of MRP II systems are highlighted and a new enhanced operational methodology based on distributed planning and control principles is introduced. Distributed Manufacturing Resources Planning (DMRP), was developed as a capacity sensitive production planning and control solution for cellular manufacturing environments. The system utilises cell based, independently operated MRP II systems, integrated into a plant-wide control system through a Local Area Network. The potential benefits of adopting the system in industrial environments is discussed and the results of computer simulation experiments to compare the performance of the DMRP system against the conventional MRP II systems presented. DMRP methodology is shown to offer significant potential advantages which include ease of implementation, cost effectiveness, capacity sensitivity, shorter manufacturing lead times, lower working in progress levels and improved customer service.

Adaptive message rate control of infrastructured DSRC vehicle networks for coexisting road safety and non-safety applications

Intelligent transport system (ITS) has large potentials on road safety applications as well as nonsafety applications. One of the big challenges for ITS is on the reliable and cost-effective vehicle communications due to the large quantity of vehicles, high mobility, and bursty traffic from the safety and non-safety applications. In this paper, we investigate the use of dedicated short-range communications (DSRC) for coexisting safety and non-safety applications over infrastructured vehicle networks. The main objective of this work is to improve the scalability of communications for vehicles networks, ensure QoS for safety applications, and leave as much as possible bandwidth for non-safety applications. A two-level adaptive control scheme is proposed to find appropriate message rate and control channel interval for safety applications. Simulation results demonstrated that this adaptive method outperforms the fixed control method under varying number of vehicles. © 2012 Wenyang Guan et al.

Introduction : the role of quality, production and technological innovation in improving competitive performance

Quality, production and technological innovation management rank among the most important matters of concern to modern manufacturing organisations. They can provide companies with the decisive means of gaining a competitive advantage, especially within industries where there is an increasing similarity in product design and manufacturing processes. The papers in this special issue of International Journal of Technology Management have all been selected as examples of how aspects of quality, production and technological innovation can help to improve competitive performance. Most are based on presentations made at the UK Operations Management Association's Sixth International Conference held at Aston University at which the theme was 'Getting Ahead Through Technology and People'. At the conference itself over 80 papers were presented by authors from 15 countries around the world. Among the many topics addressed within the conference theme, technological innovation, quality and production management emerged as attracting the greatest concern and interest of delegates, particularly those from industry. For any new initiative to be implemented successfully, it should be led from the top of the organization. Achieving the desired level of commitment from top management can, however, be a difficulty. In the first paper of this issue, Mackness investigates this question by explaining how systems thinking can help. In the systems approach, properties such as 'emergence', 'hierarchy', 'commnication' and 'control' are used to assist top managers in preparing for change. Mackness's paper is then complemented by Iijima and Hasegawa's contribution in which they investigate the development of Quality Information Management (QIM) in Japan. They present the idea of a Design Review and demonstrate how it can be used to trace and reduce quality-related losses. The next paper on the subject of quality is by Whittle and colleagues. It relates to total quality and the process of culture change within organisations. Using the findings of investigations carried out in a number of case study companies, they describe four generic models which have been identified as characterising methods of implementing total quality within existing organisation cultures. Boaden and Dale's paper also relates to the management of quality, but looks specifically at the construction industry where it has been found there is still some confusion over the role of Quality Assurance (QA) and Total Quality Management (TQM). They describe the results of a questionnaire survey of forty companies in the industry and compare them to similar work carried out in other industries. Szakonyi's contribution then completes this group of papers which all relate specifically to the question of quality. His concern is with the two ways in which R&D or engineering managers can work on improving quality. The first is by improving it in the laboratory, while the second is by working with other functions to improve quality in the company. The next group of papers in this issue all address aspects of production management. Umeda's paper proposes a new manufacturing-oriented simulation package for production management which provides important information for both design and operation of manufacturing systems. A simulation for production strategy in a Computer Integrated Manufacturing (CIM) environment is also discussed. This paper is then followed by a contribution by Tanaka and colleagues in which they consider loading schedules for manufacturing orders in a Material Requirements Planning (MRP) environment. They compare mathematical programming with a knowledge-based approach, and comment on their relative effectiveness for different practical situations. Engstrom and Medbo's paper then looks at a particular aspect of production system design, namely the question of devising group working arrangements for assembly with new product structures. Using the case of a Swedish vehicle assembly plant where long cycle assembly work has been adopted, they advocate the use of a generally applicable product structure which can be adapted to suit individual local conditions. In the last paper of this particular group, Tay considers how automation has affected the production efficiency in Singapore. Using data from ten major industries he identifies several factors which are positively correlated with efficiency, with capital intensity being of greatest interest to policy makers. The two following papers examine the case of electronic data interchange (EDI) as a means of improving the efficiency and quality of trading relationships. Banerjee and Banerjee consider a particular approach to material provisioning for production systems using orderless inventory replenishment. Using the example of a single supplier and multiple buyers they develop an analytical model which is applicable for the exchange of information between trading partners using EDI. They conclude that EDI-based inventory control can be attractive from economic as well as other standpoints and that the approach is consistent with and can be instrumental in moving towards just-in-time (JIT) inventory management. Slacker's complementary viewpoint on EDI is from the perspective of the quality relation-ship between the customer and supplier. Based on the experience of Lucas, a supplier within the automotive industry, he concludes that both banks and trading companies must take responsibility for the development of payment mechanisms which satisfy the requirements of quality trading. The three final papers of this issue relate to technological innovation and are all country based. Berman and Khalil report on a survey of US technological effectiveness in the global economy. The importance of education is supported in their conclusions, although it remains unclear to what extent the US government can play a wider role in promoting technological innovation and new industries. The role of technology in national development is taken up by Martinsons and Valdemars who examine the case of the former Soviet Union. The failure to successfully infuse technology into Soviet enterprises is seen as a factor in that country's demise, and it is anticipated that the newly liberalised economies will be able to encourage greater technological creativity. This point is then taken up in Perminov's concluding paper which looks in detail at Russia. Here a similar analysis is made of the concluding paper which looks in detail at Russia. Here a similar analysis is made of the Soviet Union's technological decline, but a development strategy is also presented within the context of the change from a centralised to a free market economy. The papers included in this special issue of the International Journal of Technology Management each represent a unique and particular contribution to their own specific area of concern. Together, however, they also argue or demonstrate the general improvements in competitive performance that can be achieved through the application of modern principles and practice to the management of quality, production and technological innovation.

Hierarchical control and performance regimes in local government

Purpose – The purpose of this paper is to consider hierarchical control as a mode of governance, and analyses the extent of control exhibited by central government over local government through the best value (BV) and comprehensive performance assessment (CPA) performance regimes. Design/methodology/approach – This paper utilises Ouchi's framework and, specifically, his articulation of bureaucratic or hierarchical control in the move towards achievement of organisational objectives. Hierarchical control may be inferred from the extent of “command and control” by Central Government, use of rewards and sanctions, and alignment to government priorities and discrimination of performance. Findings – CPA represents a more sophisticated performance regime than BV in the governance of local authorities by central government. In comparison to BV, CPA involved less scope for dialogue with local government prior to introduction, closer inspection of and direction of support toward poorer performing authorities, and more alignment to government priorities in the weightings attached to service blocks. Originality/value - The paper focuses upon the hierarchic/bureaucratic mode of governance as articulated by Ouchi and expands on this mode in order to analyse shifts in performance regimes in the public sector.

Neural Control of Chaos and Aplications

Signal processing is an important topic in technological research today. In the areas of nonlinear dynamics search, the endeavor to control or order chaos is an issue that has received increasing attention over the last few years. Increasing interest in neural networks composed of simple processing elements (neurons) has led to widespread use of such networks to control dynamic systems learning. This paper presents backpropagation-based neural network architecture that can be used as a controller to stabilize unsteady periodic orbits. It also presents a neural network-based method for transferring the dynamics among attractors, leading to more efficient system control. The procedure can be applied to every point of the basin, no matter how far away from the attractor they are. Finally, this paper shows how two mixed chaotic signals can be controlled using a backpropagation neural network as a filter to separate and control both signals at the same time. The neural network provides more effective control, overcoming the problems that arise with control feedback methods. Control is more effective because it can be applied to the system at any point, even if it is moving away from the target state, which prevents waiting times. Also control can be applied even if there is little information about the system and remains stable longer even in the presence of random dynamic noise.

Enhancing the performance of intelligent control systems in the face of higher levels of complexity and uncertainty

Modern advances in technology have led to more complex manufacturing processes whose success centres on the ability to control these processes with a very high level of accuracy. Plant complexity inevitably leads to poor models that exhibit a high degree of parametric or functional uncertainty. The situation becomes even more complex if the plant to be controlled is characterised by a multivalued function or even if it exhibits a number of modes of behaviour during its operation. Since an intelligent controller is expected to operate and guarantee the best performance where complexity and uncertainty coexist and interact, control engineers and theorists have recently developed new control techniques under the framework of intelligent control to enhance the performance of the controller for more complex and uncertain plants. These techniques are based on incorporating model uncertainty. The newly developed control algorithms for incorporating model uncertainty are proven to give more accurate control results under uncertain conditions. In this paper, we survey some approaches that appear to be promising for enhancing the performance of intelligent control systems in the face of higher levels of complexity and uncertainty.

Generalised Riccati solution and pinning control of complex stochastic networks

This paper considers the global synchronisation of a stochastic version of coupled map lattices networks through an innovative stochastic adaptive linear quadratic pinning control methodology. In a stochastic network, each state receives only noisy measurement of its neighbours' states. For such networks we derive a generalised Riccati solution that quantifies and incorporates uncertainty of the forward dynamics and inverse controller in the derivation of the stochastic optimal control law. The generalised Riccati solution is derived using the Lyapunov approach. A probabilistic approximation type algorithm is employed to estimate the conditional distributions of the state and inverse controller from historical data and quantifying model uncertainties. The theoretical derivation is complemented by its validation on a set of representative examples.

Achieving low cost and high quality aero structure assembly through integrated digital metrology systems

Measurement assisted assembly (MAA) has the potential to facilitate a step change in assembly efficiency for large structures such as airframes through the reduction of rework, manually intensive processes and expensive monolithic assembly tooling. It is shown how MAA can enable rapid part-to-part assembly, increased use of flexible automation, traceable quality assurance and control, reduced structure weight and improved aerodynamic tolerances. These advances will require the development of automated networks of measurement instruments; model based thermal compensation, the automatic integration of 'live' measurement data into variation simulation and algorithms to generate cutting paths for predictive shimming and drilling processes. This paper sets out an architecture for digital systems which will enable this integrated approach to variation management. © 2013 The Authors.

The impact of external market factors on operational practices and performance of companies

The links between operational practices and performance are well studied in the literature, both theoretically and empirically. However, mostly internal factors are inspected more closely as the basis of operational performance, even if the impact of external, environmental factors is often emphasized. Our research fills a part of this existing gap in the literature. We examine how two environmental factors, market dynamism and competition impact the use of some operational practices (such as quality improvement, product development, automation, etc.) and the resulting operations and business performance. The method of path analysis is used. Data were acquired through an international survey (IMSS – International Manufacturing Strategy Survey), which was executed in 2005, in 23 participating countries in so called "innovative" industries (ISIC 28-35) with a sample of 711 firms. Results show that both market dynamism and competition have large impact on business performance, but the indirect effects, through operations practices are rather weak compared to direct ones. The most influential practices are from the area of process and control, and quality management.

Parameter optimization for noise and vibration reduction associated with position and speed sensorless control of permanent magnet machines at low speed

With the advantages and popularity of Permanent Magnet (PM) motors due to their high power density, there is an increasing incentive to use them in variety of applications including electric actuation. These applications have strict noise emission standards. The generation of audible noise and associated vibration modes are characteristics of all electric motors, it is especially problematic in low speed sensorless control rotary actuation applications using high frequency voltage injection technique. This dissertation is aimed at solving the problem of optimizing the sensorless control algorithm for low noise and vibration while achieving at least 12 bit absolute accuracy for speed and position control. The low speed sensorless algorithm is simulated using an improved Phase Variable Model, developed and implemented in a hardware-in-the-loop prototyping environment. Two experimental testbeds were developed and built to test and verify the algorithm in real time.^ A neural network based modeling approach was used to predict the audible noise due to the high frequency injected carrier signal. This model was created based on noise measurements in an especially built chamber. The developed noise model is then integrated into the high frequency based sensorless control scheme so that appropriate tradeoffs and mitigation techniques can be devised. This will improve the position estimation and control performance while keeping the noise below a certain level. Genetic algorithms were used for including the noise optimization parameters into the developed control algorithm.^ A novel wavelet based filtering approach was proposed in this dissertation for the sensorless control algorithm at low speed. This novel filter was capable of extracting the position information at low values of injection voltage where conventional filters fail. This filtering approach can be used in practice to reduce the injected voltage in sensorless control algorithm resulting in significant reduction of noise and vibration.^ Online optimization of sensorless position estimation algorithm was performed to reduce vibration and to improve the position estimation performance. The results obtained are important and represent original contributions that can be helpful in choosing optimal parameters for sensorless control algorithm in many practical applications.^

Control of MNC environmental performance and the challenges of subsidiary network dimensions

The trend of green consumerism and increased standardization of environmental regulations has driven multinational corporations (MNCs) to seek standardization of environmental practices or at least seek to be associated with such behavior. In fact, many firms are seeking to free ride on this global green movement, without having the actual ecological footprint to substantiate their environmental claims. While scholars have articulated the benefits from such optimization of uniform global green operations, the challenges for MNCs to control and implement such operations are understudied. For firms to translate environmental commitment to actual performance, the obstacles are substantial, particularly for the MNC. This is attributed to headquarters' (HQ) control challenges (1) in managing core elements of the corporate environmental management (CEM) process and specifically matching verbal commitment and policy with ecological performance and by (2) the fact that the MNC operates in multiple markets and the HQ is required to implement policy across complex subsidiary networks consisting of diverse and distant units. Drawing from the literature on HQ challenges of MNC management and control, this study examines (1) how core components of the CEM process impact optimization of global environmental performance (GEP) and then uses network theory to examine how (2) a subsidiary network's dimensions can present challenges to the implementation of green management policies. It presents a framework for CEM which includes (1) MNCs' Verbal environmental commitment, (2) green policy Management which guides standards for operations, (3) actual environmental Performance reflected in a firm's ecological footprint and (4) corporate environmental Reputation (VMPR). Then it explains how an MNC's key subsidiary network dimensions (density, diversity, and dispersion) create challenges that hinder the relationship between green policy management and actual environmental performance. It combines content analysis, multiple regression, and post-hoc hierarchal cluster analysis to study US manufacturing MNCs. The findings support a positive significant effect of verbal environmental commitment and green policy management on actual global environmental performance and environmental reputation, as well as a direct impact of verbal environmental commitment on green policy management. Unexpectedly, network dimensions were not found to moderate the relationship between green management policy and GEP.

Development and verification of control and protection strategies in hybrid AC/DC power systems for smart grid applications

Modern power networks incorporate communications and information technology infrastructure into the electrical power system to create a smart grid in terms of control and operation. The smart grid enables real-time communication and control between consumers and utility companies allowing suppliers to optimize energy usage based on price preference and system technical issues. The smart grid design aims to provide overall power system monitoring, create protection and control strategies to maintain system performance, stability and security. This dissertation contributed to the development of a unique and novel smart grid test-bed laboratory with integrated monitoring, protection and control systems. This test-bed was used as a platform to test the smart grid operational ideas developed here. The implementation of this system in the real-time software creates an environment for studying, implementing and verifying novel control and protection schemes developed in this dissertation. Phasor measurement techniques were developed using the available Data Acquisition (DAQ) devices in order to monitor all points in the power system in real time. This provides a practical view of system parameter changes, system abnormal conditions and its stability and security information system. These developments provide valuable measurements for technical power system operators in the energy control centers. Phasor Measurement technology is an excellent solution for improving system planning, operation and energy trading in addition to enabling advanced applications in Wide Area Monitoring, Protection and Control (WAMPAC). Moreover, a virtual protection system was developed and implemented in the smart grid laboratory with integrated functionality for wide area applications. Experiments and procedures were developed in the system in order to detect the system abnormal conditions and apply proper remedies to heal the system. A design for DC microgrid was developed to integrate it to the AC system with appropriate control capability. This system represents realistic hybrid AC/DC microgrids connectivity to the AC side to study the use of such architecture in system operation to help remedy system abnormal conditions. In addition, this dissertation explored the challenges and feasibility of the implementation of real-time system analysis features in order to monitor the system security and stability measures. These indices are measured experimentally during the operation of the developed hybrid AC/DC microgrids. Furthermore, a real-time optimal power flow system was implemented to optimally manage the power sharing between AC generators and DC side resources. A study relating to real-time energy management algorithm in hybrid microgrids was performed to evaluate the effects of using energy storage resources and their use in mitigating heavy load impacts on system stability and operational security.

Design optimization of modern machine drive systems for maximum fault tolerant and optimal operation

Modern electric machine drives, particularly three phase permanent magnet machine drive systems represent an indispensable part of high power density products. Such products include; hybrid electric vehicles, large propulsion systems, and automation products. Reliability and cost of these products are directly related to the reliability and cost of these systems. The compatibility of the electric machine and its drive system for optimal cost and operation has been a large challenge in industrial applications. The main objective of this dissertation is to find a design and control scheme for the best compromise between the reliability and optimality of the electric machine-drive system. The effort presented here is motivated by the need to find new techniques to connect the design and control of electric machines and drive systems. ^ A highly accurate and computationally efficient modeling process was developed to monitor the magnetic, thermal, and electrical aspects of the electric machine in its operational environments. The modeling process was also utilized in the design process in form finite element based optimization process. It was also used in hardware in the loop finite element based optimization process. The modeling process was later employed in the design of a very accurate and highly efficient physics-based customized observers that are required for the fault diagnosis as well the sensorless rotor position estimation. Two test setups with different ratings and topologies were numerically and experimentally tested to verify the effectiveness of the proposed techniques. ^ The modeling process was also employed in the real-time demagnetization control of the machine. Various real-time scenarios were successfully verified. It was shown that this process gives the potential to optimally redefine the assumptions in sizing the permanent magnets of the machine and DC bus voltage of the drive for the worst operating conditions. ^ The mathematical development and stability criteria of the physics-based modeling of the machine, design optimization, and the physics-based fault diagnosis and the physics-based sensorless technique are described in detail. ^ To investigate the performance of the developed design test-bed, software and hardware setups were constructed first. Several topologies of the permanent magnet machine were optimized inside the optimization test-bed. To investigate the performance of the developed sensorless control, a test-bed including a 0.25 (kW) surface mounted permanent magnet synchronous machine example was created. The verification of the proposed technique in a range from medium to very low speed, effectively show the intelligent design capability of the proposed system. Additionally, to investigate the performance of the developed fault diagnosis system, a test-bed including a 0.8 (kW) surface mounted permanent magnet synchronous machine example with trapezoidal back electromotive force was created. The results verify the use of the proposed technique under dynamic eccentricity, DC bus voltage variations, and harmonic loading condition make the system an ideal case for propulsion systems.^

Hybrid Power System Intelligent Operation and Protection Involving Plug-in Electric Vehicles

Two key solutions to reduce the greenhouse gas emissions and increase the overall energy efficiency are to maximize the utilization of renewable energy resources (RERs) to generate energy for load consumption and to shift to low or zero emission plug-in electric vehicles (PEVs) for transportation. The present U.S. aging and overburdened power grid infrastructure is under a tremendous pressure to handle the issues involved in penetration of RERS and PEVs. The future power grid should be designed with for the effective utilization of distributed RERs and distributed generations to intelligently respond to varying customer demand including PEVs with high level of security, stability and reliability. This dissertation develops and verifies such a hybrid AC-DC power system. The system will operate in a distributed manner incorporating multiple components in both AC and DC styles and work in both grid-connected and islanding modes. The verification was performed on a laboratory-based hybrid AC-DC power system testbed as hardware/software platform. In this system, RERs emulators together with their maximum power point tracking technology and power electronics converters were designed to test different energy harvesting algorithms. The Energy storage devices including lithium-ion batteries and ultra-capacitors were used to optimize the performance of the hybrid power system. A lithium-ion battery smart energy management system with thermal and state of charge self-balancing was proposed to protect the energy storage system. A grid connected DC PEVs parking garage emulator, with five lithium-ion batteries was also designed with the smart charging functions that can emulate the future vehicle-to-grid (V2G), vehicle-to-vehicle (V2V) and vehicle-to-house (V2H) services. This includes grid voltage and frequency regulations, spinning reserves, micro grid islanding detection and energy resource support. The results show successful integration of the developed techniques for control and energy management of future hybrid AC-DC power systems with high penetration of RERs and PEVs.

Development of hardware in the loop real-time control techniques for hybrid power systems involving distributed demands and sustainable energy sources

The future power grid will effectively utilize renewable energy resources and distributed generation to respond to energy demand while incorporating information technology and communication infrastructure for their optimum operation. This dissertation contributes to the development of real-time techniques, for wide-area monitoring and secure real-time control and operation of hybrid power systems. ^ To handle the increased level of real-time data exchange, this dissertation develops a supervisory control and data acquisition (SCADA) system that is equipped with a state estimation scheme from the real-time data. This system is verified on a specially developed laboratory-based test bed facility, as a hardware and software platform, to emulate the actual scenarios of a real hybrid power system with the highest level of similarities and capabilities to practical utility systems. It includes phasor measurements at hundreds of measurement points on the system. These measurements were obtained from especially developed laboratory based Phasor Measurement Unit (PMU) that is utilized in addition to existing commercially based PMU’s. The developed PMU was used in conjunction with the interconnected system along with the commercial PMU’s. The tested studies included a new technique for detecting the partially islanded micro grids in addition to several real-time techniques for synchronization and parameter identifications of hybrid systems. ^ Moreover, due to numerous integration of renewable energy resources through DC microgrids, this dissertation performs several practical cases for improvement of interoperability of such systems. Moreover, increased number of small and dispersed generating stations and their need to connect fast and properly into the AC grids, urged this work to explore the challenges that arise in synchronization of generators to the grid and through introduction of a Dynamic Brake system to improve the process of connecting distributed generators to the power grid.^ Real time operation and control requires data communication security. A research effort in this dissertation was developed based on Trusted Sensing Base (TSB) process for data communication security. The innovative TSB approach improves the security aspect of the power grid as a cyber-physical system. It is based on available GPS synchronization technology and provides protection against confidentiality attacks in critical power system infrastructures. ^