Hajnalka Vaagen
email: hajnalka.vaagen@sintef.no

Bjørnar Aas
email: bjornar.aas@vissim.no

A multidisciplinary framework for robust planning and decision-making in dynamically changing engineering construction projects

Keywords: construction project, uncertainty, lean, decision-making, behavior

This paper proposes a multidisciplinary framework for robust planning and decision-making in dynamically changing engineering construction projects. The aim is to facilitate 'optimal' levels and 'trade-offs' between the major factors affecting decision-making throughout the project phases, to manage design changes and other disturbances, and to generate the maximum possible value. Offshore shipbuilding case analysis is applied to refine the model and to illustrate its value in decision-making.

Introduction and motivation

One-of-a-kind specialized vessel construction is specific for European offshore shipbuilders. To achieve economic sustainability and compete with price-focused shipbuilders, combining quality with cost effective productivity and agility to meet customer changes throughout the construction process, is key. In this context, the minimization of the use of resources and the reliable adherence to a tight schedule is challenging. The dynamic dependencies, the production processes and the involved resources are complex. Frequent changes in design and legal regulations lead to continuous adjustments in planning, procurement and execution, and define the grade of uncertainty to be dealt with on a daily basis. Deviations in judgment that depart from the standards of logic and accuracy [START_REF] Haselton | The evolution of cognitive bias[END_REF] may also worsen uncertainty and the process of decision-making. These characteristics trigger the need for competences, skills and tools to manage the disturbances and optimize the output.

Despite the growing number of issuant solutions, many of them ignore important characteristics of real systems; e.g. advanced design and engineering taking place concurrently with production [START_REF] Kjersem | Literature review on Planning Design and Engineering Activities in Shipbuilding[END_REF]. As such, many solutions lack the flexibility necessary, and are therefore perceived to be difficult to apply in practice. Industrial stateof-the-practice shows to be largely disconnected from the theory, and is more-or-less based on intelligent rules-of-thumb [START_REF] Bendoly | Behavior in operations management: Assessing recent findings and revisiting old assumptions[END_REF]. And even when methods are known and do apply (e.g. LEAN), the success of implementation relies heavily on the human behavior [START_REF] Halse | Lean Project Planning in shipbuilding: The implementation challenge[END_REF]. Lack of trust between supply chain partners, incentive misalignment, natural risk aversion, human limitations in working memory [START_REF] Hogarth | Judgment and Choice: The Psychology of Decision[END_REF] and social motivations [START_REF] Urda | Social preferences and emotions as regulators of behavior in processes[END_REF] are just a few behavioral issues that can negatively impact operational success. Even the most sophisticated technology requires judgment on design and input variables. Finally, high performance teams often demonstrate unique solutions that are not visible within engineering solutions [START_REF] Chinowsky | Social network model of construction[END_REF], and network based project organisations are not captured by existing project management literature [START_REF] Kjersem | Literature review on Planning Design and Engineering Activities in Shipbuilding[END_REF]. These challenges motivate the connection of the operational element (planning & managing tasks and resources, utilizing control functions) and the behavioral/social elements within a single framework, to facilitate robustness in decision-making and planning. Although these two elements are intertwined, the traditions in the construction industry and academic literature are to treat them separately with different focus [START_REF] Chinowsky | Social network model of construction[END_REF].

The remaining of the paper is organized as follows. Theories to connect and relevant literature is discussed in Section 2. The proposed conceptual model for robust decision-making is presented in Section 3. Case specific applications to prove the proposed model's usefulness and a list of research paths that serve to further validate the developed framework are given in Section 4, along with the conclusion.

Multidisciplinary literature study

This section highlights best practice and shortcomings in different research streams discussing robust planning and decision-making in engineering construction projects. This field is mainly steered under QMS or LEAN production principles. Most advances stop, however, at the connection of classical project management theories and techniques with lean production methodologies (originally established within the context of repetitive production), and the integration of these with innovations in information technology and ERP systems to improve information availability and quality. Despite the common understanding on 'uncertainty' and 'judgment' being major elements of construction projects, it is not clear how these are treated in existing project management literature [START_REF] Freeman | Social Aspects Related to LBMS Implementation -A Case Study[END_REF]. Lean theory -as a fundamental management philosophy using whatever methods and tools that fit the purpose to deliver customer requirements with no waste [START_REF] Ballard | Road Map for Lean Implementation at the Project Level[END_REF] -attempts to treat variability on a conceptual level; as opposed to Earned Value Management, a second widely applied project planning approach [START_REF] Emblemsvåg | Lean Project Planning in Shipbuilding[END_REF]. It is, however, unclear how this is done operationally. Recent advances, suggesting improvements and the triangulation of different methodologies exist though; see for example [START_REF] Emblemsvåg | Lean Project Planning in Shipbuilding[END_REF] and [START_REF] Hamzeh | Rethinking Lookahead Planning to Optimize Construction Workflow[END_REF]. Lack of a structured integration of 'uncertainty' and 'judgment' into the on-going discussions, however, potentially limits the success of existing approaches. For recent behavioral discussions in operations see [START_REF] Gino | Toward a Theory of Behavioral Operations[END_REF] and [START_REF] Bendoly | Behavior in operations management: Assessing recent findings and revisiting old assumptions[END_REF]. Flyvbjerg in [START_REF] Flyvbjerg | Quality control and due diligence in project management: Getting decisions right by taking the outside view[END_REF] addresses the bias of over-optimism and the planning fallacy in risk assessment in quality control in projects. Relevant project management and planning &control theories, their shortcomings and potential behavioral gaps -providing the motivation of this multidisciplinary approach to robust planning and decisionmaking in construction projects -are summarized by Table 1.

Table 1. Relevant theories, their shortcomings and potential behavioral gaps

The framework proposed to facilitate robust decision-making in dynamically changing construction projects

The framework is generated by an initial case study research for scope definition and the multidisciplinary literature study presented in Section 2. It is built around the typically critical factors that affect robustness in construction project planning and execution, and the understanding on how the behavioral element is affecting these throughout the project phases. The following example from the case shipbuilder attempts to indicate the major aspects to be captured by a multidisciplinary framework: Extensive grade of tacit knowledge and collaboration networks "built on trust" impact strategic decisions on the design flexibility offered to the customers during the construction process. Flexibility in design is, then, affecting tactical level engineering& production planning decisions. Flexibility in project scheduling in offshore shipbuilding potentially means modeling hundreds of activities, complex dependency patterns and a large number of activities with uncertainty; schedules that are difficult to follow due to bounded rationality (even when we disregard the complexity of developing such plans). The state-of-practice is more like judgmental adjustments of deterministic solutions provided by some standard software. Such multilevel interactions, involving both automated and judgmental processes, trigger the connection between the engineering and human elements. Although the importance of the human element is recognized, neither judgmental decision-making nor the discussion on the tradeoff between automated and judgmental processes throughout the project phases has so far become an integrated part of how project planning is commonly done.

Having a starting point in [START_REF] Aas | Management of Logistics Planning[END_REF], this paper assumes the major factors affecting decision-making to be information availability and solving capability. The authors in [START_REF] Aas | Management of Logistics Planning[END_REF] define efficient management of logistics planning as efficient resource allocation across planning ability and information gathering. The authors state that if for instance a company enters into a supply chain collaboration which dramatically improves information availability, or if the company implements new optimization software, the production possibility curve (in a microeconomic point of view) will shift. The underlying motivation for such actions is to increase the overall productivity since a state of inefficiency arises when there is a mismatch between the level of information availability and solving capability: hence resource utilization and exploitation is not optimal. The major aim of the framework is to enable the development of robust solutions, by 'understanding' and consciously facilitating optimal levels and tradeoffs of information availability and solving capability at all project phases. Information availability (IA) is defined here as objective information, factual and observable for the decision maker; such as, legal regulations, market and customer data, supplier data, production times, guidelines from the owners on the grade of risk to be taken, etc. Objective information is the same for multiple reporters, close to the universal truth, and as such, helpful for decision-making. Interpretation and judgment transforms objective into subjective information. The authors in [START_REF] Aas | Management of Logistics Planning[END_REF] did not focus on the human element, and hence lose the differentiation between objective and subjective information. While most decision-makers know that poor quality data fed into a computer results in poor output, few question the quality of judgments when the input information is good. This belief is opposed to recent research showing that there is substantial bias in judgments [START_REF] Hogarth | Judgment and Choice: The Psychology of Decision[END_REF]. Solving Capability (SC) summarizes over analytical and critical thinking skills to evaluate problems and to make decisions, creativity and lateral thinking skills, experience, competence and tacit knowledge held by the individuals, 'language' as communication strategies, the ability to form high performance teams for generating innovative solutions, organisational traditions, and the decision methods and tools (design, engineering planning methods& tools, information technology, others).

Figure 1 illustrates the conceptual multidisciplinary model proposed, summarizing over the factors identified to affect robust planning and decision-making. To clarify, planning and decision-making are interrelated, and to some extent discussed interchangeably, but with some distinction. Decisions can be made without planning, but planning cannot be done without decision-making since it is an embedded feature of planning. In an ideal setting the aim is objectively rational decision-making (in fact the correct behavior for given objective information in a given situation). However, it cannot be assumed that humans are able to 'see and interpret' the full picture of a problem. Compared to the task complexity the human-centered informationprocessing capacity is limited, and humans are adaptive [START_REF] Hogarth | Judgment and Choice: The Psychology of Decision[END_REF] and at best subjectively rational. The goal of modeling is to bring decisions as close as possible to subjective rationality; however, models also require human decisions on design and input variables. Their appropriateness in a given situation depends on the decision-maker's knowledge and aspiration level. In summary, the impact area of the human behaviour is substantial, as highlighted by the model on Figure 1. The objective information is subject to interpretation and prediction. The interpretations and predictions are also constrained by the sophistication level of the information technology.

Fig. 1. Conceptual model for robust planning and decision-making

Concluding the section, developments of robust solutions can be summarized by improvements in either information availability or solving capabilities. In construction projects, decision-making & planning differ along the project phases; as also information availability and solving capabilities differ. It is generally known that information availability is low at the start of the project, while the impact of changes is relatively low. Towards the end of the project life-cycle uncertainty reveals, but the ability to influence/change is low. If the conditions for maneuverability (i.e. flexibility) are not created on a higher level, unexpected events and variation orders potentially lead to process disturbance with high adaptation costs. Some of the answers to the challenges to be solved have embedded options on different levels of the project life-cycle (from product architecture, to engineering, planning and execution). The indepth understanding on how decisions, information and solving capability changes during the project life-cycle is, as such, crucial for the project's success; and a central message in this paper. To enable this understanding, the general framework provided by Figure1 is further developed to capture the project phase-specific aspects and the major connections across phases; not presented here due to space limitations. In the validation process, the offshore shipbuilding case allowed first to refine the model and, then, to prove the model by more-or-less known examples. A future step is to illustrate process improvements, by applying knowledge from the proposed model.

4

Model discussion in offshore shipbuilding and conclusion

On a general level, the proposed framework facilitates adequate levels and tradeoffs between judgmental and automated decision-making to reflect strategic orientation and competitive advantage. For example, recognizing that social capital is a critical 'asset' in enabling the competitive advantage of the case shipbuilder (i.e. design flexibility throughout the construction processes), extended focus is to be given to improving SC; by mapping the social preconditions for operational excellence to design policies that enable further success, and by integrating judgment into the decision processes (particularly in engineering and production planning, where judgmental adjustments have high impact). On the other hand, when the social capital is not critical for the competitive advantage, focus on automated decision-making is crucial.

Below we clarify how the knowledge deduced from the proposed model contributes to increased robustness in decision-making. This is done by applying shipbuilding specific examples for different uncertainty handling cases -for ex. late changes in strategic equipment specifications, like engines. Uncertainty can be risk or opportunity, and is defined by the probability of occurrence and its impact if it occurs. IA directly affects probabilities, while SC drive both impact and probability. Case 1 handles the situation where the probabilities of a particular uncertainty are changed (that is, improved IA). The probability of changes in engine specifications can be reduced by front-end loading supplier strategies, before basic design takes place; concretely, by defining the 'minimal information' needed to release a particular engineering activity. This task is judgmental, and prone to bias in data interpretation. Case 2 handles situations where the outcome of the different states is changed, by implementing actions that affect SC. The negative impact of changes in engine specifications can potentially be reduced on many levels: On a strategic level, building the vessel differently to handle different engine types (e.g. platform based architecture); on a tactical level, planning the vessel differently to enable alternative sequencing in engineering and execution (planning with and without embedded uncertainty gives structurally different solutions); in execution phase, search for the social preconditions that enable maneuverability to handle variations. Case 3 handles the situation where the decision process itself is changed, by affecting SC. Changed design and project management strategies, and explicit integration of the human element, are leading to changed decision processes. Case 4 is a special situation of Case 3, and refers to increased decision frequency; affecting both SC and IA. An extreme situation of this case is when decisions are broken down to a level where the impact of taking the wrong decision is rather low compared to the overall wealth of the company; hence, the decisionmaker can take a risk neutral attitude. Such cases assume that corrective actions can be taken for the next decision period. The Last Planner System in [START_REF] Ballard | Last Planner Update[END_REF], implemented in the context of a shipbuilder, can be seen as a case utilizing this opportunity. The danger of maneuvering in the wrong direction (often systematically) still exists, however.

Concluding the paper, in-depth understanding of how information availability and solving capabilities change during the project life-cycle, what are the 'optimal' levels and trade-offs between these, and how the human and social elements affect these, is crucial for a project's success. The proposed framework facilitates the development of this understanding to enable robustness in decision-making. The following ongoing research activities, within the context of the case shipbuilder, aim to illustrate process improvements by applying the proposed model: (i)Uncertainty planning in Lean Construction; (ii)Organisational network and behavioral studies to identify how social capital and micro level behaviour (like motivation, trust, risk attitudes, cognitive overloading) influences solving capabilities and macro-level decision-making; and (iii)Cognitive bias in project planning; (iv)Front-end-loading supplier strategies.

Acknowledgements: This paper is part of the competence building research project NextShip, under Norwegian Research Council grant agreement 216418/O70. The authors thank Jan Emblemsvåg, Senior Vice President Innovation and Process Management VARD, for valuable discussions.


Eiji Morinaga
email: morinaga@mapse.eng.osaka-u.ac.jp

Yuki Sakaguchi
email: yuki.sakaguchi@mapse.eng.osaka-u.ac.jp

Hidefumi Wakamatsu
email: wakamatu@mapse.eng.osaka-u.ac.jp

Eiji Arai
email: arai@mapse.eng.osaka-u.ac.jp

A Distributed Production Scheduling Method for Highly-Distributed Manufacturing Systems

Keywords: production scheduling, distributed method, agile manufacturing

Recent development of computer network technologies is realizing highly-distributed manufacturing systems from the hardware point of view, where each facility is computerized and manages itself autonomously by communicating with other facilities. For this new type of manufacturing systems, a new discrete event simulation paradigm has been discussed, in which sorting of events is performed by exchanging messages about their occurrence times among the facilities. To make this paradigm beneficial enough, it is desirable that re-scheduling process performed after the simulation is carried out in a similar paradigm. We have developed some production scheduling methods for flexible flow-shop production of only one kind of products with just one stage. This paper presents an improved method which can be applied to flexible flowshop of multiple kinds of products with multiple stages.

Introduction

Production scheduling is one of the key issues for achieving sophisticated design, management and operation of manufacturing systems. Numerous works have been conducted for a long time and various approaches have been discussed such as mathematical programming [START_REF] Cheng | Surevey of Scheduling Research Involving Due Date Determination Decisions[END_REF], heuristic dispatching methods [START_REF] Panwalker | A Survey of Scheduling Rules[END_REF], and so on. For detailed evaluation of a production schedule, simulation needs to be performed. Simulation techniques for manufacturing has been also discussed and many methods has been proposed [START_REF] Carrie | Simulation of Manufacturing Systems[END_REF]. Most of those researches have been conducted with the centralized concept in which the whole manufacturing system is modeled and then the optimal schedule is generated or simulation is performed based on it.

These days, it has been desired to realize agile manufacturing, which can adapt to change of situation flexibly and quickly. The centralized concept should not meet this requirement, since it would be hard to re-model the whole system and find the optimal way of management and operation for each new situation. From this point of view, distributed manufacturing systems have been discussed, where each production area is managed by a computer and the whole system is controlled by communications among the computers. In the research field of production scheduling, distributed methods using auction mechanisms [START_REF] Kaihara | Optimization Method using Combinatorial Auction for Production Scheduling with Batch Processing[END_REF], active databases [START_REF] Matsumoto | Advanced Autonomous Distributed Manufacturing System Using Active Database[END_REF], etc. have been actively discussed. Also in the simulation area, high-level architecture was proposed and distributed methods based on it have been discussed [START_REF] Inukai | Enhanced distributed-simulation using orin and hla, Mechatronics for Safety, Security and Dependability in a New Era[END_REF].

Recent development of computer and network technologies is achieving highlydistributed manufacturing systems (HDMSs) from the hardware point of view, where each facility is computerized and manages itself autonomously by communicating with other facilities. This point has been discussed in the field of manufacturing simulation, and a new discrete event simulation paradigm for HDMSs was proposed [START_REF] Fujii | A Basic Study on A Highly Distributed Simulation of Manufacturing Systems Under The Ubiquitous Environment[END_REF]. In this paradigm, events, each of which is simulated in one of the facilities, are sorted by their occurrence time and this sorting is performed by exchanging messages about the occurrence times among the facilities. To make this paradigm beneficial enough, it is desirable that re-scheduling process performed based on the simulation result is carried out in a similar paradigm. From this point of view, we have proposed a highlydistributed scheduling method [START_REF] Morinaga | A Basic Study on Highly Distributed Production Scheduling[END_REF][START_REF] Morinaga | A Basic Study on Production Scheduling for Highly-Distributed Manufacturing Systems[END_REF][START_REF] Morinaga | Basic Study on Production Scheduling Method for Highly-Distributed Manufacturing Systems[END_REF] in which priority of each facility based on the shortest processing time (SPT) rule is dynamically updated with indirect decision making and information control performed by message exchanges. This method was applied to an example and its fundamental feasibility was proven. However, this method was developed only for a very simple flexible flow-shop production where only one kind of products that require only one process are produced, and should be enhanced so that the method can be utilized in real manufacturing. This paper presents an enhanced method which can be applied to flexible flow-shop production of multiple kinds of products which require multiple processes.

This paper is organized as follows: Section 2 provides a brief explanation about the key concept of the simulation method and the conventional scheduling method for HDMSs. Section 3 describes an enhanced scheduling method which can be applied to flexible flow-shop production of multiple kinds of products that require multiple processes. In Section 4, feasibility of the proposed method is shown through a case study, and Section 5 presents conclusions.

Concept of the Conventional Scheduling Method for HDMSs

In the new discrete event simulation paradigm for HDMSs [START_REF] Fujii | A Basic Study on A Highly Distributed Simulation of Manufacturing Systems Under The Ubiquitous Environment[END_REF], the following simple algorithm was proposed for sorting events to be simulated in each simulation model implemented on each facility. Let assume that there are N computerized facilities (agents) each of which has its own simulation model. Each model has its own event whose occurrence time and priority are T i and O i . Sorting of these events can be performed by the following three steps: 1. Values of O i of all the events are set to 1, which means the highest priority. 2. Each agent (facility) broadcasts T i as a message. 3. When an agent A j , receives a message from another agent A i , A j compares its own value T j with the received value T i . Next, V j is set to 1 if T j > T i , and to 0 otherwise. Then O j is updated to O j +V j .

Figure 1 shows an example with four agents, and proves that the initial priority sequence (O i = 1, i=1,…,4) can be updated to the correct one by the proposed algorithm.

Since each model has several events and a new event is generated after the simulation for the prior event in the model, it is necessary to update the priority sequence. This dynamic determination can be also achieved by algorithms based on the same concept. Therefore the whole simulation can be performed just by message exchanges. To make this simulation method beneficial enough, it is desirable that rescheduling process performed based on the simulation result is carried out in a similar way. A major approach for production scheduling is using heuristic dispatching rules. In this approach, a schedule is generated by determining the priority sequence of facilities by the given dispatching rule and then assign a material to the facility with the highest priority. This priority sequence determination is regarded as a sorting process of the facilities according to the rule. Therefore it is expected that a distributed method of production scheduling can be established by applying the above concept and sorting algorithm to this sorting process. We have developed some methods for simple flow-shop production of one kind of products which require only one process, and fundamental feasibility of those methods was proven [START_REF] Morinaga | A Basic Study on Highly Distributed Production Scheduling[END_REF][START_REF] Morinaga | A Basic Study on Production Scheduling for Highly-Distributed Manufacturing Systems[END_REF][START_REF] Morinaga | Basic Study on Production Scheduling Method for Highly-Distributed Manufacturing Systems[END_REF]. In order to make those methods practical, it is necessary to develop them further so that they can be applied to real complex production. In the following sections, an enhanced method for flowshop production of multiple kinds of products with several processes is discussed.

Enhanced Scheduling Method for Flow-Shop Production of Multiple Kinds of Products with Multiple Processes

In this paper, flexible flow-shop production of multiple stages shown in Fig. 2 is considered. Multiple kinds of materials are transported to the buffer (or automated storage/retrieval system) of the first area one-by-one at various time period. There are several same kind of machines in the area having different performance, and an arrived material is assigned to one of the machines by the shortest processing time (SPT) rule. The material whose first process has completed is transported to the second area and then assigned to one of the machines in the area in the same way.

Each assignment of materials to one of the machines by the SPT rule in each area can be achieved by sorting the machines according to the rule. Therefore, the assign-ment can be performed by message exchanges among the buffer and the machines by applying the algorithm described in Section 2 to this sorting process (Fig. 3). We have proposed scheduling methods based on this idea by defining procedures for message exchanges among the buffer and the machines and also for updating internal states of them [START_REF] Morinaga | A Basic Study on Highly Distributed Production Scheduling[END_REF][START_REF] Morinaga | A Basic Study on Production Scheduling for Highly-Distributed Manufacturing Systems[END_REF][START_REF] Morinaga | Basic Study on Production Scheduling Method for Highly-Distributed Manufacturing Systems[END_REF]. It is possible to enhance the conventional methods so that they can be applied to the production scenario shown in Fig. 2 by improving those procedures.

Fig. 2. Considered production scenario

Fig. 3. Materials assignments by message exchanges

The improved procedures for the buffer and each of the machines in each area are shown in Figs. 4 and5, respectively. The parts described by red symbols and arrows are new components for applying this method to the production scenario in Fig. 2. Variables P and S were introduced so that each facility can distinguish received mes-sages by the ID number of process and by the kind of materials, respectively. In addition, variables B i and S i , which specify static and dynamic priority value of a machine, are defined for each kind of materials. Enhancement for considering multiple processing areas can be easily achieved just by introducing message filters so that a facility execute its own processes only if the received message is for the production process which the facility is in charge. Enhancement for considering multiple kinds of materials can be also achieved easily just by adding the same processes for arranging priority values for each kind of the materials. (Unfortunately, detailed explanations have to be omitted due to page limitation. To understand the processing flows, we would like the readers to read also [START_REF] Morinaga | A Basic Study on Highly Distributed Production Scheduling[END_REF][START_REF] Morinaga | A Basic Study on Production Scheduling for Highly-Distributed Manufacturing Systems[END_REF][START_REF] Morinaga | Basic Study on Production Scheduling Method for Highly-Distributed Manufacturing Systems[END_REF].) The proposed method was applied to an example of flexible flow-shop production of three kinds of materials with two processes. There are three machines in each area and their performance are given as in Table 1. The number of materials is 3 for A, 4 for B, and 3 for C. These materials arrive at the buffer in the first area in each 2 minutes with the order of "AABCCBBBAC". Figure 6 shows the Gantt chart of the schedule obtained by the SPT rule. The method was implemented on one computer by coding in the C language and performed by using interprocess communication, due to equipment constraints. The same schedule as in Fig. 6 was successfully generated. In this paper, the conventional production scheduling method for HDMSs have been enhanced so that it can be applied to flexible flow-shop production of multiple kinds of materials with multiple processes. Its feasibility was proven by an example. In future works, validness and advantage of this method will be discussed further by illustrations with complex scenario and comparison with conventional methods.

Fig. 1 .

 1 Fig. 1. Example of event sorting by the sorting algorithm proposed in [7]

Fig. 4 .Fig. 5 .Fig. 5 .

 455 Fig. 4. Processing flow of a buffer for material assignment

Fig. 6 .

 6 Fig. 6. Gantt chart of the schedule for the example obtained by the SPT rule

Table 1 . Processing times of the machines (unit is min.)

 1

		1-1	1-2	1-3	2-1	2-2	2-3
	Product A	5	6	7	5	6	7
	Product B	7	5	6	7	5	6
	Product C	6	7	5	6	7	5


Jane Guinery
email: jane.guinery@nottingham.ac.uk

Susan Brown
email: s.brown@nottingham.ac.uk

Martina Berglund
email: martina.berglund@liu.se

Kezia Scales
email: kezia.scales@nottingham.ac.uk

The Influence of Human Factors on Access and Scheduling of Primary Care Services

Keywords: Human factors, Scheduling, Access, Primary care

, where failure demand represents unnecessary demand placed on acute care (such as Accident and Emergency in hospitals) as well as primary care services. For eight General Practices in the UK, approaches to practice organisation, including A&S, are analysed to establish HOFs that influence service delivery and performance. Findings highlight HOFs affecting outcomes and ways in which A&S arrangements can be modified to improve them. These should inform the choice and management of effective A&S in a range of Health service scenarios, as well as for General Practices in the UK.

Challenges in Primary Care Services

With a major reorganisation in the National Health Service (NHS) in the UK, transferring the commissioning of healthcare services to Primary Care providers, the need to effectively manage Primary Care has come into sharp focus [START_REF] Goodwin | Improving the Quality of Care in General Practice[END_REF]. In particular there is currently much research on how to reduce levels of referral of patients to acute care in hospitals, where service costs are higher and represent a more serious intervention than in primary care. There have been dual and potentially conflicting responses to this, with multiple Primary care initiatives attempting to manage high levels of demand and shortfalls in health and social service provision through a combination of efficiency driven initiatives (e.g. integration of services; new technologies), and those that rejuvenate traditional practice such as extended opening hours and greater continuity of care (where GPs regularly sees specific patients).

Tensions between a drive towards efficiency and quality of service need to be rationalised. In previous studies on Lean initiatives in healthcare [START_REF] Walley | Designing Accident and Emergency Systems: Lessons from Manufacturing[END_REF], throughput was considered the most important focus for improvement, with a qualification that this should be tempered by an appreciation of Healthcare specific issues (including ensuring quality of care). However, this view has been challenged by Seddon et al. [START_REF] Seddon | Rethinking Lean Services. Process Excellence Network[END_REF], who identify that for services (including healthcare), a focus on such measures lacks sufficient critique because not all service activity is value-adding. A 'system' that may appear to be utilising available resources efficiently may in fact be expending effort on activities that are non-value adding, handling failure demand rather than what is required. According to their studies unrecognised 'failure demand', due to an inability of a service to absorb the variety of customer demands, represents the biggest cost associated with services.

In primary care the handling of patient consultations can be operationalised in a variety of ways, and there has been considerable research on appointment systems, taking a 'scientific approach' to optimise performance based on measures that include waiting times and utilisation of clinicians [START_REF] Gupta | Appointment Scheduling in Healthcare: Challenges and Opportunities[END_REF]. Such studies make assumptions on 'system' performance that exclude human behaviours (of staff and patients), and do not recognise the varied demands and expectations placed on the service. Despite this shortfall, human and organisations factors (HOFs) have been extensively studied in the context of production planning and scheduling in manufacturing businesses and supply chains [5; 6]. Here the contribution made by humans in real world situations has been studied in detail and humans have been demonstrated to perform vital roles that enable flexible responses through making effective judgment in situations where information is limited, systems/procedures are in place but problem solving and negotiation is required, and/or where constraints need to be relaxed to support competing demands in complex situations. In such scenarios people can act as gatekeepers, assessing and routing customer requests for services [START_REF] Berglund | The unsung contribution of production planners and schedulers at production and sales interfaces[END_REF]. Based on this, it is anticipated that HOFs will influence the service performance of primary care services as a whole and at an individual level, and HOFs should be influential in the selection of access and scheduling (A&S) approaches and how they are operationalised.

Further challenges in primary care relate to specific characteristics of the operation inherent to services [START_REF] Lovelock | Whither services marketing: in search of a new paradigm and fresh perspectives[END_REF]. In this context they are: simultaneity (the service is consumed as the demand is placed on it); intangibility (the service is experienced and as such the quality of service is difficult to measure); heterogeneity of demand (each customer has a unique combination of requirements and expectations and may need to be 'processed' in different ways); perishability, customers cannot be stored; and 'customers' take part in the service. Additionally the HOFs that need to be taken into account (that influence decision making and action, and ultimately the behaviour of the whole system) relate both to patients who experience the service and take part in it, and to the staff who deliver the service. This increases the complexity of A&S, as well as making service performance measurement more problematic.

The focus of this paper is on one aspect of an exploratory study investigating organisational aspects of General Practices (Practices) that influence levels of referral to acute care. The aspect of interest is the approach taken to A&S arrangements and the HOFs that influence their operation and performance.

Study objectives, scope and methodology

The original objective of this study was to identify and explore the HOFs in primary care services that influence the level of referrals to acute care. The study collected and analysed qualitative data from interviews in eight General Practices (Practices) in the UK. Practices were purposively selected to be representative, having a variety of characteristics such as list size, resourcing level, location, demographics and approaches to care. In total 48 semi-structured interviews were conducted with Practice staff in a range of roles including General Practitioner (GP), receptionist and nurse. These were transcribed and NVivo used to undertake a thematic analysis [START_REF] Guest | Applied Thematic Analysis[END_REF].

In relation to referrals, A&S arrangements emerged as a significant theme. Here, 'access' and 'scheduling' are closely related in the way they are defined. Whereas access refers to how patients manage to communicate and obtain appointments with Practice staff including GPs and nurses, scheduling relates more specifically to the decisions made by staff, procedures or systems in relation to how to prioritise and allocate appointments to patients. It is the patients' needs, and in some cases perceived needs, that will place demand on Practice resources. This raises the issue of how Practices should manage the balance between urgent and routine booking of appointments; and in the case of urgent appointments, how the urgency of appointments should be established. Without an appropriate balance patients might be able to book routine appointments in advance but fail to access care in times of acute need; or they may be able to access same-day care but struggle to make appointments to manage their chronic or anticipated health needs. In either case this might lead to a need for hospital acute care due to service failure.

This paper explores this theme; its aim is to scrutinise the alternative A&S approaches that are employed taking a combined operations management and HOFs perspective. Additional themes complementary to the analysis included: roles (of receptionists, nurses and GPs); referrals to acute care and reasons for them; patient needs, expectations and behaviour; and patient-service interaction. Data on these emergent themes was then analysed to better understand: the role of A&S arrangements in managing demand; types of failure demand and reasons for their occurrence; the different A&S approaches that have been employed to meet demand, their objectives, how they are operationalised, and the extent to which they appear to be effective; the influence of HOFs on the choice of approach and outcomes.

The Study of HOFs and Access & Scheduling Arrangements

The following sections describe findings and examine their relevance and implications on a topic by topic basis. The topics address, in order: types of failure demand; alternative A&S arrangements and their relationship to failure demand; HOFs and how they might influence A&S choices and outcomes; and the receptionist (gatekeeper) role, and how it can be enhanced to support responsiveness.

3.1

Types of failure demand and reasons for their occurrence

The analysis identified a number of types of failure demand. The most substantial, in relation to cost, was patient use of acute care hospital services. This occurred through patient self-referral (at Accident and Emergency or 'A&E') or GP referral (due to a health crisis). Clearly in many cases these referrals may be necessary, however, in relation to self-referrals many do not translate into treatment or admission and are viewed as 'inappropriate'. According to the qualitative data, Practice staff articulated the following reasons for 'inappropriate' self-referral: patients not being able to access an appointment (for example, lack of GP availability or the Practice being closed); patients calling 111 (an NHS medical hotline) and being told to self-refer to hospital as a precautionary measure; convenience where access to hospital was easier than to the Practice (whether in terms of distance, or patients perceptions that they would be seen more easily). GP referral occurred mainly due to clinical reasons, however in some cases this is a failure demand should the deterioration in a patient's condition be due to delayed access. Other reasons include inadequate support during illness from other health and social care providers. There was also evidence of concerns about limited time and flexibility for patient consultation, and lack of knowledge of a patient's specific conditions (medications and response to treatments, and circumstances) particularly where there was limited provision for continuity of care. These concerns are corroborated by findings from other studies [START_REF] Wilson | The relationship between consultation length, process and outcomes in general practice: a systematic review[END_REF].

In relation to failure demand on the Practice, lack of continuity of care is considered to be inefficient as GPs have to refer to notes and ask more questions in consultations and can miss signs of change in patients. This was particularly problematic for more elderly patients with multi-pathologies and medications. Other 'within Practice' forms of failure demand included: underutilisation of GPs and nurses due to patients missing appointments ('did not attend' -DNA); call back time of staff when they cannot respond to patients on first contact; additional consultation time due to patient deterioration; and patient waiting time (in the Practice and in telephone queues). Many of these should be addressed through effective A&S arrangements and practice.

Alternative approaches to A&S and their effectiveness

Figure 1 shows how consultations can be booked through the receptionist via telephone or face-to-face, or through online booking. The types of GP consultation available were planned appointments, urgent same day appointments, 'sit and wait' sessions (where patients come at specific times to queue to see the GP), or home visits. An alternative that some Practices employ was for the GP to ring the patient back for a telephone consultation either at a predetermined time (when the GP has purposively reserved time for this), or on an ad hoc basis. Home visits were rarely provided, as they were inefficient due to the travel time involved. Appointments could similarly be made with nurses, who generally undertook more standardised healthcare activities, e.g. monitoring and support of chronic conditions; this provided more time for GPs to handle other priority demands that required their expertise. This and other variables, such as urgency, create a need to carefully channel appointments to both the appropri-ate person and form of consultation. Bar web based appointment booking (most applicable to routine appointments), receptionists act as gatekeepers, and it is this role that needs to be understood in relation to what actually occurs regarding A&S.

Fig. 1. Access and alternative forms of consultation

The authority for making decisions regarding the urgency of a request from patients is problematic. Clinical triage can be used to alleviate pressure on the receptionist to make clinical judgements. GP or nurse telephone triage was used to differing extents to assess urgency including as a specific access stage where GPs or nurses act as first responder to a patient. In half the Practices receptionists were seen to have some level of autonomy and flexibility in also making access decisions; in others processes were more standardised and the receptionists' authority more limited.

Table 1 shows the different access arrangements available and the associated demand failures. Trade-offs of different arrangements are evident from this, as choices made to improve efficiency may have a negative impact elsewhere. For example arrangements in relation to the mix of routine and urgent appointments vary (see 'A' in Table 1). One Practice saved 'a majority' of consultation slots to same day appointments, as a way to reduce DNAs. However, as a consequence, handling of priorities is complex as requests pour in at the start of each day. Although this approach may seem to improve the utilisation of GPs, it has specific disadvantages: patient time is lost when making appointments; planned appointments are limited disrupting continuity of care; and, prioritisation is difficult to manage. This can cause anxiety and delays for patients, or deterioration in condition, and may lead to self-referral or a later need for GPs to refer patients to acute care at a much higher cost. Similarly, whilst telephone consultation (see 'E' in Table 1) seems to be efficient, used in the wrong circumstances it can impact on the quality of consultation as it tends to focus on obvious symptoms rather than holistic care. Multiple forms of service provision in combination (e.g. 'sit and wait' clinics alongside doctor's triage and ring back consultations) were used to satisfy the specific requirements of different patient groups. For example elderly patients may be more able to access or prefer to use 'sit and wait' clinics; advice on medications may be managed effectively through telephone consultation. In Face-to-face these cases Practices can be responsive to non-standard demand or situations where standard access arrangements are not effective for all groups. However, not all Practices had these alternatives, and in some the same arrangements acted as an overspill when demand was high, compensating for system inadequacy or lack of capacity.

How HOFs influence access arrangement choices and outcomes

The heterogeneity of the population impacts on the types of demand placed on primary care for different types of resource and interaction, the corresponding routes followed by patients, and their ability to access the service and make use of it. Looking at the needs of different patient groups it is evident that the 'first-come-firstserved' (FCFS) approach to scheduling can be very problematic, particularly as opportunities for access are not equal for all patient groups. For example, where access is through websites and telephone systems, this requires particular competences and equipment. Similarly, some groups' attitudes and expectations may mean that they communicate their needs less or more effectively. Some patients will also require different lengths of consultation, or prefer continuity of care; physical access including transportation may also be more problematic. More standardised A&S arrangements may not be able to recognise or take this into account. There is, therefore, a need for more flexibility to adjust appointment lengths and reserve slots for specific categories of patient and types of demand on the service. Whilst some patients may overstate, others may understate or not appreciate the urgency of their need, and nonmedical staff may feel unable to offer opinions. The type of consultation that should be offered will also vary and needs to be discerned; the patient might have a new episode requiring diagnosis, or require general advice on chronic disease management. In these cases the appropriateness of nurse appointments or telephone consultation needs to also be decided. The heterogeneity of demand and inability to customise means that some patients may inadvertently be restricted in their ability to access services, due to: limited use of technology (e.g. telephone redial), reluctance to 'bother the GP', poor communication skills, and a perceived need to see the same GP.

3.4

The role of the gatekeeper Patient demands are assessed, prioritised and routed in different ways dependent on the nature of the demand and the individual requesting the service. It was the gatekeeper's role to perform this relatively complex task. Their role in some Practices was also to reassure patients, reducing their anxiety and enabling the patient to assess and potentially manage their own condition. Sensitive and timely interactions can build the trust of patients. In these areas the human contribution in the gatekeeping role is particularly important. To prevent failure demand it is important to distinguish between types of demand placed on a service that can be handled in a standard way and those requiring non-standard attention [START_REF] Seddon | Rethinking Lean Services. Process Excellence Network[END_REF]. Receptionists can attempt to differentiate these, in some cases supporting patients as they make an decision. In some Practices this level of engagement was discouraged, with Receptionists allocating appointments based solely on a patient's perception of urgency, and often without recourse to others. However, active assessment of patients' situations was encouraged in other Practices. In these cases receptionists worked in a more autonomous and flexible way, frequently calling for input from GPs or handling aspects of an enquiry based on their own knowledge and capability (e.g. where trained to differentiate urgent and non-urgent situations). It was apparent that their ability to support patients depended not just on this empowerment, but also on the availability of appointments and the choice, flexibility and responsiveness of the arrangements, e.g. in one Practice, GPs were provided with extra time for consultations (including via telephone) and to be more accessible to other staff in the Practice, including receptionists.

Conclusion

This empirical research has identified different forms of failure demand associated with A&S; where and how HOFs (related to patients and staff) impact on A&S; and, the implications of this on the approaches that can be taken to A&S. Although data is drawn solely from UK General Practices, it has identified important aspects of A&S that may also be relevant in other health service contexts. Findings demonstrate that it is both the heterogeneity and 'non-specific' nature of demand that makes A&S problematic, and the need to recognise this when considering alternative ways in which demand can be handled. Implications of not doing so are illustrated through the failure demand types associated with A&S alternatives. In relation to how A&S might be improved, different forms of service delivery in combination have been demonstrated to address the variety of patient demands placed on them. Also, the receptionist's gatekeeper role has been found to be central in effectively prioritising and routing patients. We can postulate that to deliver a customised response and support a variety of needs, distinct cohorts of patients may need to be identified and communicated with differently either on an ad hoc or systematic basis so that appointments can be prioritised and delivered in different ways. Receptionists, as gatekeepers to the service, need to provide a range of standardised and customised responses; and their capabilities and organisational arrangements that support or inhibit them are pivotal to effective service delivery. To be flexible enough to handle heterogeneous demand and reduce failure demand it is apparent that complementary A&S approaches, gatekeeper roles, forms of service delivery, and sufficient resources need to be in place.

The study findings question any over simplification and assumptions made that exclude HOFs in the evaluation and selection of A&S approaches. HOFs provide an additional dimension to understand A&S arrangements and their subsequent performance, and this dimension needs to be included when exploring system alternatives. Related failure demand explained by HOFs can be expensive and must be factored into any A&S assessment (including models and simulations) and in choices made by healthcare practitioners when selecting, managing and implementing A&S systems.

-

  Perceived reduction in DNAs -High service utilisation -Patients queuing to make appointments -Implications of FCFS approach, particularly on specific patient groups, e.g. patient waits -Continuity of care more problematic -Patient lost time -Reception's lost time -Patient frustration/anxiety B -Pre-booked appointments -Easily managed -Allows continuity of care -Less stressful for GPs -High DNAs as patients forget or no-longer require appointments -Registrars (in training) often have to deal with urgent cases as experienced GPs are booked up! -May lengthen time to next consultation -Still need to slot in same day appointments -Under-utilisation of service -Potential quality issues around inexperienced GPs on urgent cases C -Webbooking system -Reduces demand on receptionists -Less accessible to non-computer literate (spaces filled by others), implications of FCFS Triage not operational! -FCFS approach may lead to referrals of others due to poor prioritisation D -Sit and wait -Same day access for all patients with perceived urgent needs -High service utilisation -Extra stress for doctors -Long patient waiting times -Potentially hasty consultations -Delays other activities, e.g. home visits -Continuity of care more problematic -Quality of consultation may lead to need for acute care -Lost time for patients and inconvenience may lead to self-referral E -Overspill triage ring back or consultation -Supports urgent cases and improves access -Efficient on GP time -Needs informed management & processes -Reduced thoroughness of consultation if not appropriate category -Risk of ineffective consultation may lead to need for GP acute care referral F -Home visits -Patient confidence -Holistic view of needs -Enables very ill patients to receive care -High level of resourcing; may be conducted by nurses to reduce this -Lost time for GPs in travelling to patients' homes G -Nurse appointments -Holistic view of needs -Less costly resource -Only considered appropriate for those with more standard chronic conditions -No apparent failure demand associated with these

Table 1 .

 1 -Alternative access arrangements and associated failure demands

	ACCESS	ADVANTAGES	DISADVANTAGES	FAILURE DEMAND
	A -Limited
	planned
	appointments;
	more same day
	appointments


Cecilie Peter Bjerg Olesen

Cecilie Maria Damgaard

Hans-Henrik Hvolby

Iskra Dukov- Ska-Popovska

Applicability of Planning and Control in a Port Environment

Keywords: Port, planning, coordination, non-hierarchical, maritime

des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

Historically, ports in Denmark and Europe have been owned by the government and have primarily operated as landlord for other companies and as provider of dock and crane resources [START_REF] Beresford | The UNCTAD and WORKPORT models of port development: evolution or revolution?[END_REF]. Because the port authorities have operated as landlords, they have had little focus on developing and streamlining the operations in the ports. Specifically there has been little focus on improving the competiveness of the logistic system, as they have not been taking part in this aspect, as stated by the port management of the case port. The lack of involvement in the logistic activities has meant there is no systematic coordination within the port system. In the manufacturing industry, planning and control (P&C) have been used for many years to aide companies with aligning capacity and demand as well as coping with uncertainties and inventory [START_REF] Vollmann | MANUFACTURING PLANNING AND CONTROL SYSTEMS FOR SUPPLY CHAIN MANAGEMENT: The Definitive Guide for Professionals[END_REF]. When identifying how smaller ports operate in Scandinavia, it is clear there is no tradition for using P&C methods. Most planning and execution is done ad-hoc, resulting in nonoptimal utilisation of resources. In addition, a port is a service provider, and is required to have certain resources, so it is important to ensure that these are utilised optimally.

There is a large base of literature relating to the optimisation of larger ports, see review by Stahlbock & Voß [START_REF] Stahlbock | Operations research at container terminals: a literature update[END_REF], however, Danish ports are small and medium-sized ports, which may make the use of large port literature difficult, as the complexity of the methods in the literature is often on high level.

Small and medium sized ports have not received much attention either in academia or in politics. One reason is that the focus in maritime transport research has been on globalisation. Especially the Europe/Asia container traffic have received a lot of attention, with ports as Rotterdam, Antwerp, Hong Kong and Shanghai being heavily represented in academia. The literature regarding these ports, have focussed on large-scale operations, with use of very advanced mathematical models and computer systems to control the container terminals [START_REF] Kia | Investigation of port capacity under a new approach by computer simulation[END_REF], [START_REF] Tahar | Simulation and analysis for the Kelang Container Terminal operations[END_REF] and [START_REF] Ng | Yard crane scheduling in port container terminals[END_REF]. The problem is not the quality of these methods and models, but rather that smaller ports do not have the resources required to make use of these methods, and that introducing computer systems and mathematical models in ports that are not prepared for this can have negative consequences. Another case for discussion is how much the methods benefit the small ports in terms of monetary and competitive value. With a much lower volume, the total benefit for e.g. a 1% cost reduction from a mathematical model does not have the same effect as it does in a multimillion-dollar enterprise, in terms of payback.

Therefore, there is a need for developing the small ports both in terms of strategy, but also in terms of planning and coordination, inside the port and in the supply chain. Brooks et al. [START_REF] Brooks | Coordination and Cooperation in Strategic Port Management: The Case of Atlantic Canada's Ports[END_REF] defines collaboration and coordination as the two most important parameters in smaller ports, collaboration can be defined as the strategic frame for enabling tactical and operational coordination. However since a port is a non-hierarchical system, it might prove difficult to use traditional P&C methods directly.

This paper addresses the issue of using planning and control methods for aligning capacity and demand in smaller ports. This is done by defining and understanding characteristics the port environment and analysing the applicability of P&C functions. The characteristics of a small Danish port will be analysed to find the unique profile and thereby give the opportunity to define how the different production P&C tools and methods can be applied to a port system. Further, it will provide an understanding of the nature of a port system, which can provide the knowledge of how to optimise and reconfigure it.

Theoretical background

Keeping the production data such as demand, supply, product, inventory, accounting, costing, lead-time, and routing in an integrated manner, these systems have become the central systems widely implemented in manufacturing environments. Manufacturing Planning and Control (MPC) is an overall approach, which control everything from material management, scheduling of machine capacity, suppliers, and human resources to find the best solution. Besides the physical material flow, the flow of information also needs to be taken into consideration [START_REF] Vollmann | MANUFACTURING PLANNING AND CONTROL SYSTEMS FOR SUPPLY CHAIN MANAGEMENT: The Definitive Guide for Professionals[END_REF]. MPC Systems are generally described as being divided into three time horizons, these being strategic planning, tactical planning and operational planning [START_REF] Silver | Inventory management and production planning and scheduling[END_REF], [START_REF] Koh | A knowledge management approach for managing uncertainty in manufacturing[END_REF]. Generally, planning and control (P&C) aims for matching customer demand with supply of products and materials in terms of timing, volume, and quality [START_REF] Slack | Operations Management[END_REF]. Different P&C paradigms have been proposed in the literature. However, the hierarchical P&C paradigm has become an accepted P&C structure in many medium and large companies [11], by coordinating the material flow and capacity for optimal outputs levels. This paradigm is mainly implemented with the Manufacturing Resource Planning (MRPII) framework, which is the basic logic behind the Enterprise Resource Planning (ERP) systems. The majority of the modern manufacturing firms use MRP II/ ERP systems for production P&C activities [START_REF] Stevenson | A review of production planning and control: the applicability of key concepts to the make-to-order industry[END_REF]. The MRP II framework is a well-known model that consists of interconnected material and capacity P&C functions with hierarchical guidelines, in different time frames and aggregations [START_REF] Vollmann | MANUFACTURING PLANNING AND CONTROL SYSTEMS FOR SUPPLY CHAIN MANAGEMENT: The Definitive Guide for Professionals[END_REF]. As the purpose is to define a P&C system for smaller ports, this framework will be further analysed. The MRP II system segments the P&C tasks in to three time frames; strategic (1-12 months), tactical (1 week -3 months) and operational (1-5 days), [START_REF] Silver | Inventory management and production planning and scheduling[END_REF]. The structure lies in both the length of the planning horizon as well as the level of data aggregation. The aggregation levels depends on the time horizon, and thereby the uncertainty. P&C is made for a hierarchical system setup, and since a port is not necessarily a hierarchical system, there might be some challenges in adapting this concept. However, in P&C the central tasks or functions are generic to any environment. These different planning tasks and functions are required to align a company's setup to the demand for products and handle different parts of the planning processes according to when and where it is required. E.g. aligning capacity of resources with the strategic demand, committing actual demand to different time fences in the production system's capacity and ensuring correct inventory levels at required time fences. Based on primarily Vollmann et. al [START_REF] Vollmann | MANUFACTURING PLANNING AND CONTROL SYSTEMS FOR SUPPLY CHAIN MANAGEMENT: The Definitive Guide for Professionals[END_REF]:  The long term planning is necessary for planning the overall capacity. This include equipment, buildings, suppliers, and so forth. These decisions set the parameters for responding to current and future customer demand. In the long-term planning phase, Resource Planning, Demand Management, Sales and Operations Planning, and Master Production Scheduling (MPS) functions exists.  The mid-term planning in MPC combines the detailed material planning and the detailed capacity planning in order to create a plan to satisfy customer demand. This means coordinating the supply and demand with the production capacity, levels of raw material and finished goods. Here the functions involves Detailed Material Planning, Detailed Capacity Planning, and Material and Capacity Plans. To ensure success, it is important to communicate with the customers and the suppliers about expected delivery times and quantities [START_REF] Vollmann | MANUFACTURING PLANNING AND CONTROL SYSTEMS FOR SUPPLY CHAIN MANAGEMENT: The Definitive Guide for Professionals[END_REF].  In the short-term planning the scheduling of resources (time, people, material, equipment, and facilities) is done on detail, which is required in the production plan. Here the function of the Shop-Floor Systems and the Supplier Systems exists.

All functions have varying importance depending on the environment in which they are applied, and varying detail level. Any environment will therefore have a unique profile depending on its characteristics.

3

Case description from a port system

The port system is configured around handling cargo transformation between land and sea, and is made up of several companies handling different tasks. It is necessary to understand how the port system is organised, as this greatly influences how the different tasks are planned and executed, and how information can be propagated in the port system. The amount of autonomous companies present in the operations is one of the larger challenges in attempting to plan tasks in a port. Firstly, the companies mostly operate in a craftsman's type fashion where they go from job to job, without planning the activities. This gives some challenges when coordinating the actual move of goods, as there is no clear responsibility as to who have the overall planning responsibility. This is especially true in the situations where there are several actors involved in the port operations, which is most bulk and special cargo transport transformation operations. In the container terminal there is typically one actor, but the interfacing with mainly the landside and the arrival of trucks, presents some of the same coordination challenges, such as the timing of arriving trucks and the placement of containers in the container inventory. To illustrate the different planning functions in the port system, each actor and their involvement in the system are explained:

 Shipping broker: A shipping broker is an agency that provides transport solutions for customers, either by booking transport in the market or by providing some services themselves. In some cases, the shipping agent facilitates the booking of the transport activities and coordination of these activities to meet delivery deadlines etc. In other cases, the shipping agent is only hired to handle the cargo transformation, and the shipping line or other supply chain actor books the necessary transport solutions. Seen from the port system the shipping agent often have a coordinating role.  Terminal services: This is cranes, dockworkers and other equipment required to services ships and trucks at the dockside. Different companies own these  Truck transport: These operate within or in connection to the port, the owner of the goods or a shipping broker most often hires these. Currently they arrive when it fits their own plans combined with deadlines for cargo submission and withdrawal in the ports.  Shipping line: The company that owns and operate the ship. Ships are as trucks often hired by the owner of the cargo or on their behalf hired by brokers. Some ships are however also operating on regular shipping routes. These routes are controlled by the shipping lines and are based on market demand.  Port authorities: The port authority is the owner of the land and docks. They are also the authority, which control and manage the waters in and around the port, giving permission and overseeing the ships in these waters. Further, they are landlords for most companies operating in the port system.  Support services: There are many different support services offered to both ships and companies in the port system. Ships can receive supplies, repair crews and other related services. Depending on the service, different companies handle this, and both the port authority and the shipping broker can facilitate contact for the ships.  Warehousing: Is an essential service in port, as it provides a possibility for creating distribution functions or a temporary storage space when sending and receiving large quantities of goods, which is often the case in ports. Further it also possible to use warehousing as a consolidation function, batching smaller quantities of cargo with other small shipments, so the utilisation of ship and container space becomes higher and the cost lower.

Besides the description of the different resources involved in servicing a ship, Figure 1 gives a simple overview of the resources. The resources are handled by different companies, depending on the types of goods. Common for these resources are that they are very expensive, making resource utilisation an important factor. The resources all influence each other as they are used in all operations, which also means that the operations are dependent on each other, underlining the need for coordination. One major problem regarding the organisation of resources is the many different owners with different priorities, which means the planning and the coordination is segmented from the resources. Even though, some of the ports P&C system can be defined on a hieratical level, this is not entire the possible due to the structure of the port system. Furthermore, planning becomes even more challenging as most of the actors in the port system uses calendar based planning, where they put in ship arrivals and make loose plans regarding resources and personnel around these events. The information in the calendar is based on sales orders issued through the shipping agent, and the port authority's monitoring system for approaching ships. However, the information available in the monitoring system is not actively communicated to all parties in an organised way, which means it is not used to keep the existing plans updated. Further, the knowledge about how to handle the specific orders is based on silent knowledge accumulated within the operational staff in the port.

Olesen et al [START_REF] Olesen | Framework for Information sharing in a Small-to-medium Port System Supply Chain[END_REF] proposes an implementation of a form of centralized platform for information sharing. This will improve the coordination that handles information about the flow of goods. In the current setting there are challenges with communicating this information to the workers early enough to plan other activities before committing resources to service an incoming ship. Also not all resources need to be present as soon as the ship docks. By centralising the information flow, it will be easier to make a feasible plan for the common resources, and thereby easier for companies at the port to plan based on ship arrival and crane and dock availability. However, to ensure the correct use of such an information-sharing tool, it is important to have an overview of the different functions needing information. Therefore, the following will give a structured overview of the planning activities in the port system.

Defining the planning environment in a port system

The reason for utilising P&C is to be able to create a model that allows configuration of a planning environment in a port. A review of intermodal operations research have been done by Macharis & Bontekoning [START_REF] Macharis | Opportunities for OR in intermodal freight transport research: A review[END_REF], where they also focus on the three time horizons of strategic, tactical and operational which align with the effort in this paper, however, in this paper the planning functions from the MPC are added to be able to relate operations with a planning task. Planning is necessary, as ports are very dynamic environments were a lot of different transport actors come and go every day. This builds in an uncertainty into the system that lacks a mechanism to plan and re-plan activities according to demand and delivery of goods and services in a close to real-time manner. Another issue regarding the lack of P&C in ports is the ability to measure, evaluate and compare operations in the port with other similar ports. By creating a structured environment with variables and functions, the performance control will also be structured and be comparable.

The port system and the cases have been described to show the need for planning and coordination in the small to medium sized port environment. With that in mind the cases are related to the planning functions mentioned in Vollmann [START_REF] Vollmann | MANUFACTURING PLANNING AND CONTROL SYSTEMS FOR SUPPLY CHAIN MANAGEMENT: The Definitive Guide for Professionals[END_REF]. The main challenges found in the case port are:

 Aligning port activity with incoming ships and trucks  Pushing information about activities in the port to external partners  Planning of shared resources and individual activities  Coordination and sequencing In reference to the case description, it is also evident that the planning functions are relevant in the port environment. However, the use of MRP as the engine is not relevant as there is no BOM and thereby material requirements calculations. Further, the MPC model also implies a hierarchical setup, which is not present in most ports. These factors means that MPC is not directly transferable to this context. However, since it is a system made up of resources, processes, products and demand it is comparable to the MPC when looking purely at the planning functions. The MPC functions are translated in Table 1 to a comparable function in a port setting. It is important to stress that it is only the concept of aligning capacity and demand in all planning faces, and this approach does not expect to make use of all methods and tools attributed to each planning function in a P&C environment.

The frame of the MPC model is very descriptive of what is relevant when planning in any type of environment, as it at simplest is a time fencing of activities segmented into resources, capacity and materials. In the port system, resources and capacity also apply and materials are the goods passing through the port.

The MPC framework is hierarchical, which the port system is not. Therefore, this cannot be applied directly on the port system. However, all planning activities are still relevant to all industries. Therefore, only the hierarchical perspective of the framework cannot be applied. Table 1 shows the function of the port system applied in a P&C contests, with especially focus on the MPC framework.

Relating the port system to the planning functions and the time frames, it becomes evident that one of the major challenges is to assign responsibility for the different planning functions. However, since the port system is fragmented, most of these functions in the strategic and tactical layer would have to be handled by the port authority and the shipping broker, as these have contact with all partners. The order and timing of actions and the execution of these (Operational) Port Data system Vendor systems Information sharing system between all actors related to specific jobs. (Operational)

Discussion and Conclusion

The paper discuss P&C as a method for coordinating activities in a port. The elements of the well-described MPC are used to illustrate the planning functions and the aggregations levels. Because of the expectation of a hierarchical system structure in the MPC model, it is not entirely applicable to the non-hierarchical port system. However, the general purpose of the planning functions is to align capacity and demand in different aggregations, and this is what the port system need. Therefore, the port system should make use of the overall approach of the MPC planning functions, placed in the port context as in Table 1. The motivation behind this approach is to utilise a well-known model to create a general approach for ports to align their activities. Some of the elements within the MPC model are not relevant in relation to a port service system, such as the MRP logic, but the method for aligning capacity and demand on the three different time scales, is highly relevant. When the timing of a ship arrival changes the information has difficulty permeating through the port system. The reason for this is two-fold, firstly is the lack of information sharing amongst the partners. Secondly is the lack of methods to understand, plan and re-plan the activities based on the available information. This is why the ability to think in strategic, tactical and operational time frames are essential, as well as the ability to match capacity with demand and operational execution.

To utilise the P&C features, a method is created that will allow a structured approach to identify how to handle certain events within a P&C system. This is done by defining the tasks in a port, e.g. loading and unloading containers, stone or grain. The difference between these tasks is not large, but the demand and supply structures are different, and the need for equipment and resources are also different. Further, each type of goods going through the port have a unique requirement in terms of services and tools required to perform these services.

This paper presents a new way of looking at planning and coordination in a port and this method needs to be tested in a port system. Further, a framework based on these findings needs to be created, in order to present a planning and coordination model that applies fully to a port system, considering the non-hierarchical structure.

Fig. 1 .

 1 Fig. 1. The boxes are resources and companies, and the circle represents the port system.

Table 1 .

 1 An interpretation of the MPC system in a port context.

	Port Function	MPC Function Purpose
	Port System Plan-	Sales and opera-	The port strategy based on input from demand
	ning	tions planning	and resource planning (Strategic)
	Resource Plan-	Resource plan-	The alignment of resources to port strategy and
	ning	ning	forecasted demand (Strategic)
	Hinterland man-	Demand manage-	Creating and finding demand in the port's hinter-
	agement	ment	land (Strategic)
	Port system ca-	Master production	The aggregation of the strategic demand sorted
	pacity check	scheduling	into time fences with capacity check on the re-
			sources. (Tactical)
	Port Data System	Detailed material	The commitment of resources to certain ship arri-
		planning	vals in a common data platform. (Tatical)
	Port capacity	Detailed capacity	Booking of capacity in relations to production or-
	planning	planning	ders within time fences. (Tactical)
	Arrival manifest	Material and ca-	List of ship arrivals, with details of cargo and ac-
		pacity plans	tors, sorted into time fences. (Tactical)
	Coordination/ se-	Shop floor sys-
	quencing	tems