(Abstract 003 – 0055)
DEVELOPING A DECISION SUPPORT SYSTEM (DSS) FOR WORKLOAD CONTROL (WLC): A CASE STUDY
Mark Stevenson[*] and Linda C Hendry
SIXTEENTH ANNUAL CONFERENCE OF POMS
CHICAGO, IL
APRIL 29th – MAY 2nd 2005
Name:Mark Stevenson
Institution:Lancaster University
Address:Department of Management Science
Lancaster University Management School
Lancaster University
LA1 4YX
U.K.
E-mail:
Tel:00 44 1524 593707
Fax:00 44 1524 844885
Name:Linda C Hendry
Institution:Lancaster University
Address:Department of Management Science
Lancaster University Management School
Lancaster University
LA1 4YX
U.K.
E-mail:
Tel:00 44 1524 593841
Fax:00 44 1524 844885
Developing a Decision Support System (DSS) for Workload Control (WLC): A Case Study
Mark Stevenson and Linda C Hendry
Department of Management Science, Lancaster University Management School (LUMS),
Lancaster University, U.K., LA1 4YX
ABSTRACT
The paper focuses on the development of a Decision Support System (DSS) based on the concept of Workload Control (WLC) and describes the strategy taken to overcome a number of prerequisites for the successful implementation of a Production Planning and Control (PPC) concept. Issues addressed include grouping machines and determining capacities. The DSS has been designed for a MTO company, where, given the complexity of production and highly customised nature of jobs, planning must be initiated at the customer enquiry stage. Other PPC approaches often neglect this stage, while most empirical WLC research concentrates on the job release stage, assuming that accurate delivery dates and an appropriate mix of jobs have already been determined. This case study adds to the available literature by looking specifically at implementing WLC from the customer enquiry stage and by adapting an existing methodology to the requirements of the current manufacturing climate.
Keywords:Production Planning and Control (PPC), Workload Control (WLC), Decision Support System (DSS), Make To Order (MTO), Job Shop.
1. INTRODUCTION
Workload Control (WLC) is a Production Planning and Control (PPC) concept designed for complex production environments, such as the job shop. WLC can lead to the reduction of shop floor throughput times and Work-In-Progress (WIP); see Land & Gaalman (1996), and originates from the concept of Input-Output Control (I/OC); see Wight (1970). In general terms, the input of work to the shop floor is controlled in accordance with the capacity of work centres (the output rate), using workload bounds, in order to regulate and maintain a stable level of WIP. This is facilitated through the use of a pre-shop pool and a job release stage. Despite the concept receiving much attention in the literature, only a handful of case studies have emerged (Bertrand & Wortmann 1981; Fry & Smith 1987; Bechte 1988; Hendry et al. 1993; Bechte 1994; Wiendahl 1995; and Park et al. 1999), leading to a need for further empirical research (see Bertrand & Van Ooijen 2002; Kingsman & Hendry 2002).
In order to effectively implement WLC in practice, it is important to satisfy a number of prerequisites and build a Decision Support System (DSS) tailored to meet the particular needs of a company. For example, it can be necessary to group machines and improve the flow of information, while accurate estimates of capacity are also required. Furthermore, it can be important for management to determine norms and parameters, such as expected shop floor queuing times. Such requirements are not uncommon and are essential for the successful implementation of other PPC concepts. For example, Material Requirements Planning (MRP) has previously been criticised for requiring accurate estimates of capacity (see Wiendahl 1995), while Constant-Work-In-Process (CONWIP) relies on accurate feedback data in order to regulate throughput (see Stevenson et al. 2005). Hence, such implementation issues are relatively generic amongst PPC concepts. Overcoming such issues is important for increasing the amount of empirical evidence involving innovative PPC concepts, including WLC.
This paper addresses implementation issues of this type in the context of the development of a DSS for a Make-To-Order (MTO) company based on the concept of WLC. A strategy to develop and implement PPC concepts is described, highlighting the depth of issues that must be addressed for an effective innovative PPC concept to be widely applied in practice. This includes some theoretical developments of the particular approach to WLC discussed. The paper begins by describing the WLC concept used in the DSS before Section 3 examines implementation insights from previous empirical research. Section 4 discusses the proposed methods to overcome implementation complexities in two key areas: (a) grouping machines and (b) determining capacities. Features of the DSS, leading to theoretical development of the WLC concept, are presented in Sections 5 to 9, before conclusions are drawn in Section 10.
2. HIERARCHICAL BACKLOG CONTROL FOR MTO COMPANIES
WLC stabilises the performance of the shop and makes it independent of variations in the incoming order stream (Bertrand & Van Ooijen 2002), resulting in a more manageable shop floor, consisting of a series of short queues. Most WLC concepts are built around the use of a job release mechanism, see, for example, the review and classification of Order Review and Release (ORR) policies by Bergamaschi et al. (1997). Such releasing mechanisms have a significant effect on the performance of the production system, reducing WIP and lead times (Hendry & Wong 1994); jobs are only released onto the shop floor if released workload levels will not exceed preset maximum limits, whilst ensuring jobs do not stay in the pool too long, in order to meet Delivery Date (DD) objectives.
However, due to the degree of customisation offered by MTO companies, production often does not commence until after a customer enquiry is received. As a result, lead times are longer than for Make-To-Stock (MTS) companies and take on strategic importance. Hence, planning and control at the customer enquiry stage is considered particularly significant (see Hendry & Kingsman 1989), in order to stabilise lead times and aid DD determinations. Therefore, to maintain control in a MTO environment, the job release stage can benefit from supplementary control at the preceding decision levels of customer enquiry and job entry. Previous successful case studies have often concentrated on supporting the release function, thus failing to provide adequate decision support for MTO companies.
A WLC methodology for MTO companies has been developed at the Lancaster University Management School (LUMS) to incorporate customer enquiry and job entry control in a hierarchical structure (hereafter referred to as the LUMS approach). The empirical research project described in this paper uses the LUMS approach as the basis for the DSS developed for a MTO company, thus providing an insight into some of the practical implications of implementing the LUMS approach. A hierarchy of backlogs is incorporated in this approach as follows, where each is a subset of the next: (1) Released Backlog: The Total Work Content (TWC) of jobs on the shop floor; (2) Planned Backlog: The TWC of jobs awaiting materials, in the pre-shop pool and on the shop floor; (3) Total Backlog: A proportion of the TWC of unconfirmed jobs, in addition to the TWC of all accepted jobs. Figure 1 below summarises the hierarchical control framework, indicating the key production stages to control (before allowing the foreman to take control of the shop floor). For a complete description of earlier versions of the LUMS approach, see Hendry & Kingsman (1989 and 1991), Kingsman (2000) and Stevenson & Hendry (2005).
Figure 1: Hierarchical backlog control framework
In particular, the LUMS approach supports the quotation and negotiation process in an attempt to ensure realistic DD’s are quoted to prospective customers, based on the current workload (im)balance and capacity of the shop. At the lower level, the approach can be described as an aggregate approach as the workload of a job is attributed to the released backlog of each work centre at the moment of job release (see Stevenson & Hendry 2005). The backlog at a work centre hence includes load in transit (indirect load) and load on hand (direct load) without distinguishing between the two. For a complete review of PPC concepts and their applicability to MTO companies, see Stevenson et al. (2005).
3. AN OVERVIEW OF EMPIRICAL WLC RESEARCH AND IMPLEMENTATION
Contemporary research in the field of WLC is predominantly simulation based, for example, Perona & Portioli (1998), Henrich et al. (2003) and Henrich et al. (2004). All of the aforementioned studies explore practical issues, and hence are directly geared towards the application of WLC in practice. However, empirical research is considered vital to the validation of such simulation results. This section provides a brief overview of insights obtained from the limited number of previous case studies, highlights the gaps in the evidence gathered and hence illustrates the need to address implementation issues to aid further empirical research.
One of the first reported case studies of WLC was presented by Bertrand & Wortmann (1981). The authors developed an aggregated production control theory and information system and applied this to the diffusion department of a semiconductor plant producing integrated circuits. However, the planning and control requirements of the semiconductor industry are rather unique: for example, the industry is renowned for a process of re-circulation (see Fowler et al. 2002), making it difficult to generalise these results. Furthermore, given the fast moving and increasingly competitive environments for which WLC is designed, more contemporary research is required.
Fry & Smith (1987) presented a limited case study implementation of a bottleneck-oriented I/OC method for a tool manufacturing job shop, focusing on job release. The authors report reductions in WIP and backlogs, an increase in customer service and quoted lead times more than halved. The authors describe how the approach was used on one product line (pliers), representing 40% of total sales. However, other product lines may have different routings and bottlenecks. The authors offered six practical steps towards implementation: (1) Change from local efficiency measures to global throughput measures; (2) Identify bottlenecks to determine the maximum system throughput; (3) Set maximum inventory levels between work stations; (4) Reduce production lot sizes; (5) Work on the correct items; (6) Set input equal to output. However, although the method was shown to work in a job shop, products appear standardised, reducing the complexity of planning and control. Park et al. (1999) present a second bottleneck-oriented case study, developing a WLC based DSS to aid DD determinations for a large rotating machinery shop. The DSS monitors the workload of the bottleneck operation in line with the principles of the Theory of Constraints (TOC). However, it is considered that in a job shop, controlling the workload balance across all work centres is important, such a system may also suffer from the ‘wandering bottleneck problem’. The authors offer little explanation of how in depth issues involved at the implementation stage were addressed. For further details of bottleneck load oriented WLC, see Enns & Prongue Costa (2002).
The complex probabilistic WLC methodology used by Bechte (1988 and 1994) and by Wiendahl (1995), known as Load Oriented Manufacturing Control (LOMC), determines the indirect load of a work centre based on the probability of a job arriving at a downstream work centre in the corresponding planning period. Bechte (1988) reports, for example, the convergence of planned and actual lead times. The author touches on implementation start up effects, similar to those commonly found in simulation; when implementing a DSS, it will take time to capture the current status of the shop and for appropriate parameters to be determined. Bechte (1994) describes a number of software requirements; for the implementation of LOMC, a new calendar was installed for lead time calculations and backwards scheduling along with new work centre and transaction data files. Wiendahl (1995) emphasises the need to provide information regarding, for example, machine availability, personnel capacity and feedback information through improving the flow of shop floor information. The author provides six useful steps towards implementation: (1) Manufacturing Analysis; (2) Manufacturing Process Improvement; (3) Feedback Accuracy Improvement; (4) Monitoring System; (5) Checking Present Manufacturing Control; (6) Load Oriented Manufacturing Control. However, the author also explains that at least a year must be spent at each step to ensure permanent improvement can be expected, and if some steps have already been taken, the minimum time for implementation is two years. Wiendahl (1995) also explains that companies must give up the ‘traditional concepts’ of manufacturing, in other words, the successful implementation of WLC may hinge on overcoming cultural issues within the company. However, it is considered that in practice, managers are likely to prefer simplicity to the more complex probabilistic approach. A method that is over-sophisticated may be misused through lack of understanding or neglected over time.
3.1 Further Required Empirical Research: Issues to Explore
Aggregate load methods, such as the LUMS approach, have received criticism for relatively poor performance in simulations as routing variability increases; see, for example, Oosterman et al. (2000). However, there is no WLC method that performs better than the others under all tested conditions (Cigolini & Portioli 2002) and the additional impact of customer enquiry control provided by the LUMS approach can only be determined through implementation in practice. However, in order to facilitate empirical research, a number of issues need to be overcome. Firstly, the original concept plans workload requirements on an aggregate weekly level (see Hendry & Kingsman 1993), however, with growth in the MTO industry and high levels of competition driving down lead times, a weekly plan may provide insufficient control for the shop floor. Secondly, accurate and up to date feedback information regarding the progress of jobs on the shop floor is required, but this can be difficult to provide under complex shop conditions. Short lead times also mean that the interval between periodic releases is likely to reduce towards a more continuous release policy, further increasing the need for up to date feedback information. Thirdly, the methodology requires more foresight in order to reflect the future load of the shop. Fourthly, WLC concepts require certain norms and parameters to be set, however, these can be difficult to determine. Finally, the LUMS methodology does not exist in the form of a contemporary Windows-based DSS. Therefore, this paper presents a DSS based on the LUMS approach for a small MTO company to address these shortcomings and provide an insight into some of the practical complexities of developing and implementing an innovative PPC system. Through empirical research, the DSS described in this paper also seeks to support the encouraging simulation results of the LUMS approach by Hendry & Wong (1994) and Hendry et al. (1998). Also note that a comparable empirical research project is currently being undertaken at the University of Coimbra (Portugal), see Silva & Magalhaes (2003) for initial details.
4. PREPARING FOR WLC: The Case Study Company
The case study company, hereafter referred to as Company X, is a small, but growing subcontract precision engineering MTO Company based in the North West of England. The company operates as a general job shop, with facilities such as CNC milling, drilling machines, centre lathes and CAD/CAM technology. Company X has steadily grown in terms of the number of employees and annual turnover, currently employing thirty people with a turnover of approximately 1.5 million Euros, and hence can be described as a small company within the framework of SME’s. Typical customers of the company are in the aerospace, automotive and defence industries. When quoting DD’s, the company do not directly consider the capacity of the shop and current workloads, and simply state a lead time of approximately three weeks; as a result, the company is overloaded and under pressure to improve DD adherence. Company X has previously considered the adoption of an Enterprise Resource Planning (ERP) system; however, management rejected this idea due to the ‘one size fits all’ mentality of large and expensive computer packages. It was anticipated that as the size of the company increases, the current ad-hoc planning measures would have to be replaced with a cost effective planning and control system, such as WLC.
4.1 Grouping Machines
The shop floor of Company X consists of 23 machines, making it difficult to ensure that the necessary level of detailed feedback information required by the LUMS approach is provided. Up to date feedback information is required in order to update the position of jobs on the shop floor and reduce the released backlogs of work centres that have processed a particular job. Henrich et al. (2003) explain that WLC concepts often assume the immediate feedback of information; this is an assumption that can be satisfied in simulation, however is unlikely to be the case in reality. As a result it is necessary to group machines into work centres where data can be collated and reported back at regular intervals, prior to release decisions. Grouping machines can also make the system more manageable, as, for example, fewer norms, such as backlog length restrictions, have to be determined and monitored.
Henrich et al. (2004) explain that grouping interchangeable machines also means that the decision of designating jobs to a particular machine can be delayed, thus providing flexibility. In addition, alternative job routings do not have to be considered, as similar machines will already be grouped together using one backlog of work. However, in reality, a company often accumulates machines over time, hence they vary in age, specification, processing speeds and set up times, making it rare that they are completely interchangeable, thus distorting the capacity of the work centre. As a result, to maintain control over information feedback, it can be necessary to group semi-interchangeable machines.
Employees within Company X are commonly skilled in one or two value-adding activities (covering a number of machines), while employees can also simultaneously operate more than one machine at once. Hence, employees tend to be allocated to a single machine or a pair of machines, and can be reallocated to a discrete number of alternatives. Therefore, grouping machines can provide greater flexibility for allocating work and for allocating operators to resources. A limited number of rarely used machines have no employees directly assigned to them (milling, grinding, sawing and drilling). When these operations are required, an employee from a specific area is moved across to complete the task.