LM has central importance to this thesis which aims to test the applicability of lean production scheduling and control techniques in non-repetitive production systems. For this reason, Chapter 2 presents extensive research into the lean paradigm with the
view to develop strong insight into its overarching principles and constituent components.
Initially, the chapter sets to investigate the origins of leanness in the post World War 2 Japanese manufacturing. This historical overview is intended to unveil the context in which the precursor of LM, i.e. the TPS was conceived. The discussion identifies challenges faced at the time by Toyota and its focus on waste elimination as a means of securing their future in an extremely volatile economic environment. A wide spectrum of TPS tools is reviewed drawing attention to JIT production and its prerequisites including mixed model sequencing, workload balancing, production in small batches, set-up time reduction and the notion of production flow.
TPS and JIT were initially confined within Toyota and its supply chain until the second oil crisis. It was mainly then that Toyota’s resilience and ability to sustain its growth attracted the attention of its national and international competitors. The chapter points to landmark publications by Sugimori et al. (1977) and Ohno (1988) and their influential role in the dissemination of TPS in Japan. It proceeds to explore initiatives led by research and professional groups including the IMVP and RMG which boosted the diffusion of TPS in western manufacturing and led to the emergence of the LM paradigm.
The evolution of leanness is reviewed by analysing the central notions of waste and value within the context of the lean enterprise, that is, the most contemporary form of the lean paradigm. In line with the lean enterprise model, lean thinking is extended beyond the shop-floor into the product design, R&D, HR and other departments of a manufacturing company as well as its procurement, marketing and sales functions which govern the relationships with its supply chain and customer base.
The chapter further focuses on the implementation of LM and attempts to identify the complete array of goals, principles and techniques that need to be adopted to allow a successful lean transformation. The analysis reveals a plethora of schemes proposed for the classification of TPS, JIT and LM tools and practices. The rationale for embarking on the lean transformation journey is discussed by exploring the financial and manufacturing performance differential resulting from the adoption of leanness. Performance metrics and benchmarking schemes introduced to support manufacturers in assessing their degree of leanness are also considered.
The final sections of this chapter review empirical research concerned with recent industrial applications of LM. These overall produce overwhelming evidence in favour of the success of LM although a few failed implementations are also identified. Despite
the growing support LM received over the years, it is surrounded by a number of misconceptions. These relate to the overall scope of the lean paradigm, its potential in relation to rival manufacturing paradigms and limitations of its applicability within manufacturing and other sectors.
Overall, the extensive review of LM has produced a number of significant findings, which are summarised below:
1. The continuing interest of academics and practitioners in LM and the considerable number of recent industrial applications of LM is a clear manifestation of its currency.
2. Originally introduced as the TPS, leanness has not remained static. This would be incompatible with one of its fundamental principles, i.e. that of continuous improvement. Leanness itself has over the years evolved into its current form represented by the lean enterprise model.
3. The precise nature of LM is still a subject of great controversy. Leanness has been described as a set of goals, methods, processes, tools as well as a philosophy, strategy, program and mindset. Through the historical overview presented in this chapter, it becomes evident that leanness is both a manufacturing and business philosophy. This philosophy sets the long term strategic objectives e.g. waste elimination, value maximisation, continuous improvement etc. that lean adopters strive to achieve.
4. From the operational perspective and similarly to its precursor i.e. the TPS, LM is a multi-faceted production system. Its true power lies in the synergistic effect of its complementary constituents. Several of these constituents, for instance, setup time reduction using SMED techniques are important prerequisites for its successful operation as they provide the necessary infrastructure for other key lean elements, e.g. JIT production and pull control.
5. LM is still being discounted to a manufacturing toolbox. This myopic approach has led to many piece-meal and ad-hoc implementations of some of its techniques. Unless LM is embraced holistically, its true potential is compromised.
6. A lot of the controversial aspects of LM can be attributed to the lack of a universal definition of what constitutes leanness. Definitions and classification schemes attempting to differentiate between lean principles and techniques and organise them into clusters abound and cause further ambiguity.
7. This chapter has produced considerable evidence showing that in most cases, failed implementations of LM are due to poor organisation and planning of the
lean implementation project. This review highlighted the importance of clear mission, top management support, employee engagement and training, good communication, commitment to the lean ethos, continuous improvement and cultural change as key preconditions for a successful lean transformation.
8. Reported failed implementations of LM are also attributed to the lack of perseverance and strong sustainability focus. The lean implementation project does not have a definitive end. It is an ongoing journey.
9. There still exists anecdotal evidence regarding the suitability of leanness for non-repetitive manufacturing systems. HVLV production is argued as one of the areas in which leanness has limited applicability. This thesis aims to test the transferability of LM into non-repetitive, non-serial HVLV production systems. 10. The comparison of LM with rival manufacturing paradigms has shown that in
their majority the latter are founded on the principles of LM. Rival systems are also often compared to an outdated and narrow perception of the lean production model.
11. The numerous successful implementations of LM provide substantial evidence in support of its world-class manufacturing status and ability to sustain strategic competitiveness.
As production scheduling and control are at the focal point of this thesis, Chapter 3 reviews hierarchical production planning and control systems and the functions performed in their context. The impact of shop-floor layout, product diversity and demand response policy on scheduling and control decisions is considered. Scheduling and production control systems designed for repetitive flow-shops are reviewed and contrasted to those suitable for non-repetitive job-shops. The most prevalent forms of production control, namely push and pull are discussed and applications of pull control in non-repetitive production lines are examined in detail.
3 Production Planning and Control (PPC)
Manufacturing firms rely on schedules to satisfy customer demand. Failure to meet promised due-dates compromises the quality of customer service and can lead to irreversible loss of customer confidence. Effective schedules allow firms to utilise their resources efficiently. They can free up capacity which in turn enables firms to be versatile and agile in the way they respond to customer orders. Good scheduling brings competitive advantage in a fast-changing manufacturing sector facing the immense pressures of globalisation.
Scheduling problems aim to satisfy multiple conflicting objectives. Their combinatorial nature results in a vast solution space. Scheduling is performed in volatile production environments where unexpected events can cause deviations from established production plans. Control is a function integrated with scheduling to monitor the execution of plans. It ensures work flows through work centres as planned. One of the latest innovations in the area of operations control concerns pull control mechanisms introduced in the context of JIT. Similarly to JIT, pull control was designed specifically for repetitive mass production systems. The purported success of pull control is the main driver behind the investigation of the feasibility of its extension to non-repetitive production systems.
This chapter reviews the scope of operations scheduling and control and discusses functions performed in their context. Initially, it draws attention to product volume and variety and the impact these have on the way manufacturing organisations configure their production systems and schedule their operations. Scheduling is reviewed in the context of repetitive and non-repetitive production systems, i.e. flow-shop and job-shop environments respectively. The review points out intriguing commonalities. It further enables the development of a conceptual job-shop scheduling framework. The discussion extends to main forms of production control, focusing mainly on pull control. A detailed analysis of the operating principles of pull control mechanisms is presented followed by a comparative review of their performance. The review identifies three pull control mechanisms which remain at the focal point of research to date. The main contribution of this chapter to the thesis is the conceptual scheduling framework which coupled with the three identified pull control mechanisms provide the design parameters for the agent-based simulation model developed in chapter 5 to test the operation of pull control in job-shops.
The next section reviews three main factors, namely nature of demand, order fulfilment policy and shop-floor configuration which influence scheduling practice. Section 3.2 provides an overview of the planning and control hierarchy in which operations
scheduling is carried out. It stresses the reliance of scheduling on outputs generated by MRP planning systems. Loading and sequencing formulated as optimisation problems in the flow-shop and job-shop scheduling literature are discussed in section 3.3. Section 3.4 provides an in-depth analysis of the mechanics and performance of pull control policies. Finally, section 3.5 draws conclusions to this chapter.
3.1 Contextual factors influencing production scheduling
Scheduling affects every aspect of human venture from simple everyday tasks to complex operations and services across most industrial sectors. Gupta (2002) admits that due to its multifaceted nature, scheduling classifications and definitions abound. According to Kempf et al. (2000, p. 204) in manufacturing settings, production scheduling is concerned with “assigning scarce resources to competing activities over
a given time horizon to obtain the best possible system performance”. Manufacturing
resources generally comprise machines, tooling, material handling systems, human operators etc. however, this analysis will specifically focus on machines. Activities are manufacturing operations that require processing on machines. They are determined by decomposing the products that need to be manufactured within a certain time period into their respective sets of operations. These need to be processed in predetermined sequences (imposed by technological constraints) on certain types of machines. Due to resource limitations that characterise every production system, activities that require scheduling often have to compete for specific machines especially those which tend to be heavily utilised. The output of the scheduling process, namely, an operations schedule, specifies the timings and order that activities need to be carried out by machines and influences the manner in which WIP will flow through the system.
Scheduling generates allocations of activities to available machines. The aim in scheduling is to optimise system performance with respect to a wide range of often conflicting objectives e.g. on-time completion of operations to meet due dates, maximisation of machine utilisation, and minimisation of WIP levels within the system (Wiendahl et al., 2005). Managing the trade-offs between these objectives and seeking an optimal or near optimal scheduling solution in a vast solution space has led to the recognition of the intrinsic complexity of scheduling problems and their classification as Non-Polynomial (NP) hard (Leung, 2004).
Wild (1994) suggests that the nature of scheduling problems and associated solution techniques are influenced by the following three factors: (i) the nature of demand for manufacturing products, (ii) the orientation and order fulfilment policy of the production
system (iii) the type of manufacturing process and its effect on shop-floor configuration. These influencing factors are discussed further in the following sections.
3.1.1 Nature of demand
Manufacturing is the physical transformation of raw materials (inputs) to goods (outputs) sold to customers. Goods such as automobiles, electrical appliances, personal computers etc. are end products with complex structures consisting of various sub-assemblies, components and parts. Demand for such integral components is dependent on the demand for finished products. In contrast, demand for finished goods is independent and cannot be established based on demand information already available (Martinich, 1996).
This distinction is particularly relevant in scheduling. Operations scheduling is primarily concerned with manufacturing activities associated with dependent demand items, that is, the processing of raw materials and their progressive transformation into parts, components and sub-assemblies of products. Independent demand inventories are normally controlled by periodic review policies designed to replenish inventory when levels reach predetermined reorder points. Conversely, the high number of dependent demand items handled in any given factory setting call for an entirely different approach, in fact one which is capable of handling large volumes of data. MRP is the computerised system typically used to manage dependent demand inventories (Jacobs and Weston, 2007).
3.1.2 Production orientation and order fulfilment policy
Demand for finished goods is either generated externally in the form of orders placed by customers or created internally so that manufacturing products can be stocked to meet future customer orders. In the first case, customers specify the range of goods to be manufactured and timing of production. Internal scheduling is performed to ensure production of the goods ordered is completed on time to meet due dates and is therefore directly influenced by external demand. Wild (1994) classifies such scheduling systems as externally oriented and contrasts them to internally oriented systems where production is scheduled on a speculative basis in anticipation of future demand. It is evident that whilst externally oriented systems need to be able to respond to demand quickly, there is higher flexibility in internally oriented systems where scheduling of activities is not time-limited.
Proposing a similar classification, Markland et al. (1998) maintain that production systems can be differentiated based on the amount of processing they perform following receipt of orders. Manufacturing companies where procurement of raw materials and fabrication of parts are only instigated once customers have placed firm orders are known to implement a MTO policy. Such a policy of responding to demand is mostly appropriate for companies capable of customised production offering a wide range of “tailor-made” products.
A policy diametrically opposed to MTO is MTS, adopted by manufacturing companies which offer a limited range of highly standardised products. As the name of the policy suggests, production aims to create an inventory of finished goods which is used to fulfil customers’ orders. Therefore, the processing performed by such systems is not associated with firm but rather anticipated demand. MTS companies rely heavily on forecasting models which use historic sales data to estimate the product mix and volume as accurately as possible. Following the convention proposed by Wild (1994), MTO production systems can be classified as externally oriented whereas MTS factories and their scheduling operations are internally oriented.
Porter et al. (1999) identify three more classes of order-driven policies. Assemble-to- Order (ATO) implies that adopting firms produce standardised modular components which are assembled according to customers’ specifications to offer model variations of the same finished product. The two main types of operations performed by ATO systems are fabrication and assembly, with the first aiming to create stock and the second initiated in response to customer orders. This explains why ATO systems are considered to be a compromise between MTS and MTO. Engineer-to-Order (ETO) and Design-to-Order (DTO) systems are less frequently adopted. They rely on more customer input into product development and customisation. ETO companies produce a standard product range with optional modifications which are available upon request. DTO systems allow individual clients to get involved in the research and development of products thus maximising their uniqueness. Nevertheless, ETO and even more so DTO result in considerable lengthy design and production lead times.
Focusing on this particular point, Slack et al. (2010) study the underlying differences between these policies by examining the total amount of time customers need to wait between placing an order and receiving the finished products. In doing so, they compare the production throughput time (P) which is the total time required to procure raw materials, manufacture and deliver the product with demand time (D) that is, the length of time between placing an order, processing and transporting it to the customer.
As illustrated in Figure 3.1, the graduation from make-to-stock to make-to-order results in a lower P:D ratio pointing to longer customer waiting times.
Source: Slack et al. (2010)
Figure 3.1 P:D ratios in different demand response policies
3.1.3 Manufacturing process and shop-floor configuration
Stevenson (2006) recognises that scheduling functions are highly dependent on the volume of production, which in turn largely determines the type of manufacturing operations (processing) performed at a given manufacturing facility. He broadly categorizes production systems into high, intermediate and low volume. There is an inverse relationship between production volume and product variety. Low volume systems are mainly associated with high mix production whereas high volume systems are dedicated to the production of small ranges of goods. Mass production lines are typical examples of high volume systems.
Reviewing developments in contemporary manufacturing operations management, Gunasekaran and Ngai (2012) highlight a shift of focus from medium level and variety production in the 1970s to maximising variety and minimising volume from 2010 onwards. This is remonstrated on the basis of the challenges facing modern manufacturers with competitive advantage linked to product individualisation as opposed to customisation. In order to accommodate different levels of production
P D P D Make-to-Stock Make-to-Order Purchase Deliver Make Purchase Deliver Make Time Manufacturing Activity
volume and variety, processing equipment needs to be physically arranged into appropriate production layouts.
Layouts by fixed position are typically encountered in project settings. Project manufacturing is concerned with the protracted production of unique (often one-off) large scale and high value products (Smith, 2008). The production of heavy machinery, aircrafts and ships is undertaken in such layouts. Due to the nature of the end product, the latter remains stationary whilst all necessary resources e.g. labour, raw materials, equipment etc. move around its fixed position.
Process manufacturing requires functional layouts, typically job-shops where general purpose machines performing similar processing operations e.g. drilling, milling, grinding etc. is grouped together in discrete workstations occupying designated areas of the shop-floor. Products typically manufactured in job-shops are machine tools or components for a wide range of industries including aerospace (Scallan, 2003). Contrary to project manufacturing, in process layouts the product moves through different sections of the factory in batches and the actual routing is determined by the sequence of processing steps that need to be completed on different workstations. Such shop-floor configurations allow great flexibility as they can accommodate the production of a high variety of products requiring work of a jobbing nature in small